Scenescapes
Scenescapes
How Qualities of Place Shape Social Life
Daniel Aaron Silver and Terry Nichols Clark
The University of Chicago Press
Chicago & London
Daniel Aaron Silver is associate professor of sociology at the University of Toronto at Scarborough. Terry Nichols
Clark is professor of sociology at the University of Chicago.
The University of Chicago Press, Chicago 60637
The University of Chicago Press, Ltd., London
© 2016 by The University of Chicago
All rights reserved. Published 2016.
Printed in the United States of America
25 24 23 22 21 20 19 18 17 16 1 2 3 4 5
ISBN-13: 978-0-226-35685-3 (cloth)
ISBN-13: 978-0-226-35699-0 (paper)
ISBN-13: 978-0-226-35704-1 (e-book)
DOI: 10.7208/chicago/9780226357041.001.0001
Library of Congress Cataloging-in-Publication Data
Silver, Daniel Aaron, author.
Scenescapes : how qualities of place shape social life / Daniel Aaron Silver and Terry Nichols Clark.
pages cm
Includes bibliographical references and index.
ISBN 978-0-226-35685-3 (cloth : alkaline paper) — ISBN 978-0-226-35699-0 (paperback : alkaline paper) — ISBN
978-0-226-35704-1 (e-book) 1. Social ecology. 2. Sociology, Urban. 3. Place (Philosophy)—Social aspects. 4. Situation
(Philosophy)—Social aspects. I. Clark, Terry Nichols, 1940– author. II. Title.
HM861.S56 2016
304.2—dc23
2015031996
This paper meets the requirements of ANSI/NISO Z39.48-1992 (Permanence of Paper).
Contents
Acknowledgments
1 Setting the Scene
2 A Theory of Scenes
3 Quantitative Flânerie
4 Back to the Land, On to the Scene: How Scenes Drive Economic Development
5 Home, Home on the Scene: How Scenes Shape Residential Patterns
6 Scene Power: How Scenes Influence Voting, Energize New Social Movements, and
Generate Political Resources (with Christopher M. Graziul)
7 Making a Scene: How to Integrate the Scenescape into Public Policy Thinking
8 The Science of Scenes (with Christopher M. Graziul)
Notes
References
Index
Acknowledgments
This book emerged from the distinctive scenes around the University of Chicago, which
facilitates wide-ranging and open-ended intellectual collaborations, friendships, and
explorations. Our own scene centered on weekly Wednesday evening meetings for nearly
a decade. Multiple cohorts of talented visitors, postdocs, undergraduates, and graduate
students have been regular participants, physically and via Skype.
Scenescapes is emphatically a collective product of the “scenius” of these meetings.
Certain individuals have nevertheless offered key support that we acknowledge. Larry
Rothfield was a leader in the project’s initial formulation when he was faculty director of
the Cultural Policy Center. Clemente Navarro helped refine the theory and develop
methods for analyzing scenes. He has been a constant partner in developing scenes
analyses in new and exciting directions with his research teams in Spain.
The number of students and assistants who have contributed to the research behind
Scenescapes is too long to list, though we are deeply grateful to all. Some 10–15 assistants
each year for almost a decade helped assemble, check, double-check, and analyze the
scenes database. Some stood out in leadership roles. Sam Braxton and Eric Rodgers led in
consolidating our ever-evolving merge files and in helping with initial hypotheses. Chris
Graziul was a constant resource on methods and analyses. Meghan Kallman and Whitney
Johnson coordinated many tasks. Jessica Gover provided crucial support in preparing the
manuscript.
International scenes project collaborators include for Canada, Diana Miller and Matt
Patterson; for France, Stephen Sawyer; for Spain, Clemente J. Navarro Yáñez; for South
Korea, Chad Anderson, Miree Byun, Wonho Jang, Seokho Kim, and Jong Youl Lee; for
Japan, Yoshiaki Kobayashi, Chihiro Shimizu, and Shinya Yasumoto; for Poland, Marta
Klekotko and Magda Kubecka; and for China, Di Wu, Jefferson Mao, Cary Wu, and Rui
Lin.
Financial support was generously provided by the Cultural Policy Center, Urban
Network, University of Chicago, Social Sciences and Humanities Research Council
(Canada), and University of Toronto; and financial support to the international scenes
collaborators came from many other sources, especially the cities of Paris and Seoul, as
well as the National Research Framework (Spain), Polish Ministry of Science, Chinese
Academy of Sciences, and Chinese Ministry of Civil Affairs.
We benefited from conversations and feedback from friends and colleagues, often at
meetings and workshops where we presented drafts of chapters, such as the International
Sociological Association, American Sociological Association, American Political Science
Association, Social Science History Association, Midwest Political Science Association,
European Sociological Association, European Urban Research Association, International
Conference on Cultural Policy Research, Social Theory, Politics, and the Arts, and
University of Chicago Urban Forums’ “Modeling Local Area Processes.” We are
especially grateful to those who read and commented on earlier drafts of the chapters (or
their forerunners): Stephen Sawyer, Erik Schneiderhan, Diana Miller, Matt Patterson, John
Paul Rollert, Clemente Navarro, Jon Baskin, Bill Daniels, Terry Nicholson, Elena Bird,
Ilana Ventura, Filipe Silva, Forest Gregg, and three anonymous reviewers for the
University of Chicago Press.
Anita Silver read every sentence of the manuscript word by word, subjecting it to an
exacting Mom Test that issued the final verdict on readability and comprehensibility. We
thank her for this and more.
Some portions of this book draw from or adapt previously published work, which we
acknowledge here:
Silver, Daniel, Terry Nichols Clark, and Clemente Jesus Navarro Yanez. “Scenes: Social Context in an Age of
Contingency.” Social Forces 88 (July 2010): 2293–2324.
Silver, Daniel. “The American Scenescape: Amenities, Scenes and the Qualities of Local Life.” Cambridge
Journal of Regions, Economy and Society (2012): 97–114.
Silver, Daniel, and Terry Nichols Clark. “The Power of Scenes: Quantities of Amenities and Qualities of
Places.” Cultural Studies 29, no. 3 (2015): 425–49.
Silver, Daniel, and Terry Nichols Clark. “Buzz as an Urban Resource.” Canadian Journal of Sociology 38, no.
1 (2013): 1–32.
Silver, Daniel, and Diana Miller. “Contextualizing the Artistic Dividend.” Journal of Urban Affairs 35, no. 5
(2013): 591–606.
1
Setting the Scene
A group waves their hands across a storefront window as motion-sensing devices play
music to their movements. Down the street, a few dozen enthusiasts have an impromptu
outdoor paint fight. Upstairs in a dive bar pool hall, droning electronica plays amid
flashing lights while people with brightly colored hair and tattoo-covered arms eat vegan
food. This is not the Latin Quarter, Greenwich Village, or Haight-Ashbury. It is East
Toronto. Similar scenes exist in many other cities.
Yet these scenes of indie art, cafes, and electronic music are not the only ones. In
bucolic Ave Maria, Florida, all roads lead to a central cathedral and the coffee shop TV is
tuned to Mass. The Village, near Vallejo, California, transforms scenes from the paintings
of Thomas Kinkade into an urban aesthetic promising “calm, not chaos. Peace, not
pressure.” Celebration, Florida, evinces a Disney Heaven of safety and cleanliness. Scenes
like these, and many others, are part of our everyday social environment. They factor into
crucial decisions, about where to work, where to open a business, where to found a
political activist group, where to live, what political causes to support, and more. How,
why, and how much? This book provides tools for thinking about these questions, and
some answers.
“Scene” as the Aesthetic View of Place
This book is about scenes, what they are, where they are, why they matter. “Scene” has
several meanings. One usage emphasizes shared interest in a specific activity: the “jazz
scene,” the “mountain climbing scene,” and the “beauty pageant scene.” Another
highlights the character of specific places, typically neighborhoods or cities: the “HaightAshbury scene,” the “Wicker Park scene,” and the “Nashville scene.”
Our approach to “scene” extends these first two meanings, seeking a more general level
of analysis. As a first step on this analytical ladder, think about a neighborhood as a film
director, painter, or poet might. There are people doing many things, sitting in a cafe,
entering and exiting a grocery, milling about after a church service, cheering the home
team. Then ask what style of life, spirit, meaning, mood, is expressed in all of this. Is it
dangerous or exotic, familial or avant-garde? How could others share in that spirit,
experience and embrace its meaning sympathetically, or reject it? What, in other words, is
in the character of this particular place that links to broader and more universal themes?
The Simple Ability to Perceive and Participate in Scenes Contains
Remarkable Complexities
This third meaning—the aesthetic meaning of a place—is our focus. It implies a way of
seeing that we are all familiar with to some degree. Different places feel different. You can
see the differences pass by as you walk, or bike, or drive (slowly, with the windows down)
around most any city. Here, fashionable people in high-end restaurants are getting ready
for a museum gala or film opening—a glamorous scene. There, families in blue jeans are
setting up picnic tables in a park for a barbecue—a neighborly scene. The list could go on,
and it will, in later chapters.
Yet however familiar and intuitive such scenes are, they are quite remarkable in a
number of ways that are worthy of reflection: namely, in that (1) they are possible at all,
that we can coordinate our behavior based on them; (2) we can recognize and differentiate
among them; and (3) they matter for things we care a lot about, like why some people and
places are more economically successful than others, among other things. Let us consider
each of these in turn, as they structure the chapters that follow.
Embedded Meaning Makes Scenes Possible
For the first, how scenes are possible at all, think about what happens when something
goes wrong. Imagine for a moment two different scenes.
One is in a jazz club. The lighting is dark, glasses are clinking, smoke is in the air,
people are talking, the band is playing and joking with the crowd between sets, cocktail
waiters and waitresses artfully dodge around the tables, black-light paintings line the wall,
and the audience spills out into the street, where groups stand smoking cigarettes and
eating food from a nearby takeout.
The other is a classical music performance. The audience sits up straight, silent absent
the occasional cough, wearing suits, ties, and formal gowns; the orchestra, in black and
white, sits at stiff attention following the conductor’s cues; fragile chandeliers hover
overhead; and all are surrounded by architecture that evokes neoclassical temples,
designed to provoke awe and reverence.
Box 1.1 Classical Musicians Are Experimenting with New Venues and New
Music
In Silver Spring, a cellist plays in duo with electric guitar, their music wrapped in an envelope of reverb
and static from the computer processors onstage. In Baltimore, a saxophone and bass clarinet perform
acoustic compositions by acclaimed 20th-century composers in tandem with new electronic pieces by
younger ones, interspersed with a live contribution from a DJ. And in Washington, a composer who wants
to form a new-music group turns, not to conservatories, but to Craigslist.
Classical music is thought of as a world of formal wear, red velvet seats and Mozart concertos. But
young classical musicians here and elsewhere are increasingly exploring additional ways to express
themselves. Once upon a time, young conservatory musicians wanted to grow up to play as soloists with
major orchestras. Today, many of them are forming bands instead.
[They] represent an attempt to break down the traditional concert format, which can seem stiff and offputting to the younger crowd whom all musicians these days would like to attract. The New York
performance space Le Poisson Rouge, a club-style venue that features contemporary and classical music
acts, is drawing attention nationwide. Locally, groups look hopefully at Busboys and Poets, or the
Millennium Stage, or the basement of the Harman Center, while the Sonic Circuits Festival, a celebration
of the eclectic and electronic, holds some events at the visual arts center Pyramid Atlantic in Silver Spring.
“The crowd [at Busboys and Poets] is so mixed, all the young people, the vibe in there,” said Nick
Kendall, a 31-year-old violinist with the bluegrass-jazz-uncategorizable, classically trained string trio Time
for Three.
— Anne Midgette (2009)
Now imagine a mistake: a musician hits a wrong note or plays during a rest. What
happens in the jazz club? Chances are the other musicians continue to play. The “wrong
note,” while unintended, is a kind of welcome surprise. It interrupts usual improvisational
habits, and the musicians launch into a new key, a new time signature, that they had not
expected. The audience cheers, and afterward, the “offending” musician takes a special
bow, all have a laugh and pour another round of drinks.
And during the classical performance? If a New York Philharmonic violinist
accidentally played during the pauses in the great duh-duh-duh-duh theme in Beethoven’s
Fifth? The audience would gasp, the offender’s face would go beet red, and if the show
did not stop right then, as soon as it was over, he or she would be looking for a new line of
work. Critics would write about the horror of the experience.
How do people know how to respond appropriately in such different scenes? It is
somewhat amazing. Likely few audience members would have met before. Especially in a
big city, they will be from different regions, ethnic backgrounds, ages, and so on. To be
sure, the musicians know each other better, and their training may lead them to expect
certain things from one another. But take the same jazz musicians and put them in a
classical performance, or in a wedding ceremony for that matter, and watch much of their
“jazziness” be replaced by more formal standards. Put classical musicians in a crowded
bar and watch the reverse occur.
We know how to respond to the situation appropriately partly because something in the
situation tells us how to do so. Think again of the jazz club and the Beethoven concert, of
what is going on not only in the venues but also outside and around them. The whole
situation, from the movement of the waiters to the design of the building, from the nearby
restaurants to the posture of the musicians, conspires to “say” things about how to behave:
“Be ready for a surprise, express yourself!” in the jazz scene; “Follow established forms
elegantly, with refinement and grace!” around the concert hall. Messages, or mantras, like
these are written into the situations through which we routinely move, encoded in our
streets and strips. They make phenomena like “scenes” possible. Chapter 2 explores these
multiple meanings of scenes in more detail.
Aesthetic Intuition plus the Transformation of Desires into Activities and Amenities
Makes It Possible to Recognize Different Scenes More Clearly
And here is a second remarkable feature of scenes: we can recognize their subtle aesthetic
differences, often without much ado. For instance, in Toronto, scenes with an offbeat,
avant-garde feel (think pop-up art galleries and indie rock clubs) are near others with a
more glamorous, exhibitionistic, uninhibitedly flamboyant ambiance (think nightclubs and
velvet ropes). Separated by only a few hundred yards, participants in both scenes tend to
have similar demographic and educational profiles. Yet these scenes can be experienced as
separate worlds—a difference marked linguistically when the indie-hipsters brand the
clubbers as “905ers,” somewhat sneeringly imputing to them a suburban area code.
Similarly strong aesthetic and cultural distinctions recur elsewhere. We make them all
the time, often without any explicit or official markers. Some cities do try to formally
define their scenes. Chicago under Mayor Daley II installed distinctive sculptures and
icons for different neighborhoods, even rocket-shaped towers with rainbow stripes for its
gay neighborhood, Boystown. Many cities post signs like “Entertainment District” or
“Chinatown” to flag what type of scenes to expect there.
But by and large these official signs merely recognize formally scenes that are already
known. The “real” scenes spill out over the official signage. Their “true” characters are
more complex, and sometimes more in dispute.
Still, the differences are there, and we see them. How? Partly because we are not only
“cognitive” creatures. We also react to distinctive aesthetic cues. We perceive the world
not only as neutral facts and data, but also as full of value-charged objects about which we
render judgments: a beautiful sunset, an ugly smokestack, an inspiring skyline, a tacky
strip mall.
The philosopher Immanuel Kant pioneered in identifying this aesthetic component of
mental life in his aptly titled Critique of Judgment. It has been a recurrent, if often
subterranean, theme in psychology and social science, but seldom addressed explicitly.
Perhaps the key figures here are the Gestalt theorists.
Two of their ideas are crucial for understanding scenes. First are what they called
“affordances.” The idea is that things “afford” certain responses; they “call out” to us. A
door handle “asks” to be turned; a set table “invites” us to sit and enjoy a meal.
Second is the idea of “the Gestalt” itself. We see and understand elements of our world
holistically, rather than summing the component parts. If we see a tree, for example, we do
not see branches, then leaves, then a trunk, and then add all those things together in our
minds to make a tree. Instead, we see the tree as a complete entity.
The various elements of the situation, that is, come to us in some kind of totality, where
each part fits, like each stroke of a painting. This means that, while things “afford” certain
responses, what they “say” varies situationally. The “same” gesture acquires different
meanings in different contexts. In one situation, a raised hand is a friendly greeting. In
another, it is an act of aggression.
While these abilities to take in the holistic meaning of a scene and to respond to the
behavioral cues embedded in objects may be in some sense hardwired into our mental
architecture, they are also clearly subject to historical and social variation and refinement.
Anthropologist Grant McCracken lists “fifteen ways of being a teenager in North America
in 1990: rocker, surfer-skater, b-girls, Goths, punk, hippies, student government, jocks,
and on and on.” Economic historian Deidre McCloskey compares this to the 1950s: “You
could be mainstream or James Dean. That was it” (McCloskey 2006, 26). This expanding
multiplicity of styles is not written in nature, even if the potential may in some sense be
genetic.
Box 1.2
Man is a consuming and sportive animal as well as a political one.
— John Dewey, The Public and Its Problems ([1927] 1954, 139)
The Empire State Building may be recognized by itself. But when it is seen pictorially it is seen as a related
part of a perceptually organized whole. Its values, its qualities as seen, are modified by the other parts of
the whole scene, and in turn these modify the value, as perceived, of every other part of the whole. There is
now form in the artistic sense.
— John Dewey, Art as Experience ([1934] 2005, 141)
The things of the world are not simply neutral objects which stand before us for our contemplation. Each
one of them symbolizes or recalls a particular way of behaving, provoking in us reactions which are either
favorable or unfavorable. This is why people’s tastes, character, and the attitude they adopt to the world and
to particular things can be deciphered from the objects with which they choose to surround themselves,
their preferences for certain colours or the places where they like to go for walks.
— Maurice Merleau-Ponty, The World of Perception (2004, 63)
Historical and social changes into the twenty-first century—some of which are
summarized in figure 1.1—have rendered more persons more sensitive to subtle aesthetic
differences, which have become more sharply delineated in day-to-day experience. The
great economist Alfred Marshall outlined the general logic. He called it the transformation
of “wants” into “activities.” By “wants” Marshall meant basically what we would today
call “preferences.” These are, so to speak, in your head (or heart, or gut—somewhere
internal), such as desire for comfort and security. But “wants” can also include the wish to
have a home that is not cramped but somehow elevating. Or to live near friends who
stimulate you and give you a sense of intimacy and warmth.
Figure 1.1
For most persons through most of human history it has been difficult to realize many if
not most of their wants, or even to clearly distinguish among them. Growing general
affluence, safety, health, education, and mobility change this drastically, as do the
declining, or at least less automatic, influence of the extended family, of the Company
Man, of traditional religion, and the concomitant rise of various types of relativisms in
culture, science, and spirituality, from Picasso, to Einstein, to Esalen.
Box 1.3 The Expressive Revolution Takes Hogtown and the Pork Butcher to
the World
Historically Victorian and blue-collar cities like Toronto and Chicago are changing.
Ernest Hemingway wrote a column for the Toronto Daily Star. He once complained, “Christ, I hate to
leave Paris for Toronto, the city of churches” (Lemon 1985, 57). There are now in Toronto more holistic
health centers, acupuncturists, yoga studios, and martial arts schools per postal code than there are churches
and religious organizations.
In 1975, Saul Bellow wrote, “There were beautiful and moving things in Chicago, but culture was not
one of them” (69). In 1976, Milton Rakove described Chicago as “Dick Daley’s town. Uncultured and
parochial . . . not an Athens, neither a Rome, nor a London, and never a Paris” (Rakove 1975, 41). In 2003,
Mayor Daley II had the street-level bus stops and rail entrances redesigned to match those in Paris. In 2009,
the director of the National Endowment of the Arts said, “Mayor Daley should be the No. 1 hero to
everyone in this country who cares about art” (Jones 2009).
— The authors
This is a quite general shift, from a life experienced as necessary to one experienced as
contingent. One symbol is the workplace, less determined by physical givens like rivers
and lakes and more by proximity to people and skills. Another is the typical career path,
which more frequently involves half a dozen different jobs rather than lifelong attachment
to one firm. Still another is religion, where, as Robert Putnam and David Campbell have
shown, there are more “liminals,” people who move back and forth in and out of various
faiths. And even for those who stay in the religion of their forebears, that religion, as
philosopher Charles Taylor argues, must increasingly acknowledge and define itself
against the availability of many, many other viable spiritual options. Style, personal
meaning, and aesthetics all accordingly increase in personal and social salience.
More wants become more effective. As they do, organizations and occupations spring
up to meet them; they become amenities. The vague desire for an uplifting home becomes
a home décor shop and an interior design firm. The diffuse wish for intimate warmth
becomes a patio supply store, a family-friendly restaurant, and a smiling bartender.
Amenities like these become platforms for living practices. Now there are people who
devote themselves, day in and day out, to excellent interior design or maintaining
wonderfully welcoming restaurant ambiance. You can dedicate your life to indie rock or
body art. And a whole menagerie of social types acquires sharper form. Hipsters and
Bobos, Patio Men and nerds, metrosexuals and soccer moms, and many more. Our
analysis of the World Values Survey (in chapter 6 and elsewhere) shows that across dozens
of countries there has been a dramatic increase in cultural organization membership and a
diversity of value shifts.
As vague preferences become practices and amenities, they are transferred from our
heads and enter into the world. We can then see them there, before us. They crystallize in
real organizations and occupations, like tattoo parlors, twentieth-century art galleries,
cafes, or fishing lodges. They are listed in the yellow pages, pay taxes, have conventions,
and sometimes are even counted in national censuses. You can look them up on Google
Maps to get a feel for what types of activities characterize a place.
And the social scientist can document and analyze them. For instance, as figure 1.2
shows, in Canada between 1999 and 2008 the number of musical groups, dance
companies, independent artists, and performing arts establishments doubled, dramatically
outpacing a total average growth rate of 20 percent for all businesses. Sports and health
facilities and clubs also rose steeply; zoos, record stores, bowling centers, and amusement
arcades were among those contracting. Building on this type of information, we can
identify local differences in kinds of amenities, classify them as different types of scenes,
and investigate the causes and consequences of their variations.
Figure 1.2
This figure shows the percentage change in the total number of various arts, culture, and leisure establishments across
Canada between 1999 and 2008. For example, dance companies and musical groups nearly doubled in this period. The
black bar shows change in total businesses as a benchmark: everything above it grew faster than total businesses did;
everything below it either grew more slowly or contracted during this period. These are six-digit NAICS categories,
descriptions of which are available at the Statistics Canada website. Source: Statistics Canada, Canadian Business
Patterns (1999–2008).
Much of this book does precisely this type of analytical work. For now, the key point is
to build from the more intuitive, experiential basis of scenes; you can feel them, some as
sacred, others as entertaining, perhaps others as corrupting. We recognize these differences
in scenes not only because of some innate aesthetic intuition, not only because we are
desiring creatures with a broad range of wishes and hopes, but also because scenes have
become woven into the fabric of our distinctive social environments.
As Scenes Become More Sharply Delineated, Their Effects Become Stronger
If scenes emerge as effects of various wants and preferences, when crystallized as
amenities and activities, they become potent causes. This is because when scenes become
more sharply delineated around us, they become more likely to worm their way into the
center of all sorts of everyday decisions—decisions about where to live, to work, to locate
a firm, what political party to support, what causes to fight for, and much more. This
points to the wide-ranging social consequences of scenes.
Consider first residential effects of scenes. At the turn of the twentieth century, these
would have been less salient for most Americans. The typical town might have a pub or
two; the typical person, a farmer, would need several hours travel to get there. Leisure
time would be scarce. No doubt churches often rang with the sounds of music and families
told stories to one another. Still, if you had the chance to move, or even to think about why
you would stay where you are (to think about your residence in the subjunctive, we could
say), issues like jobs, farming and forestry, ethnic and religious heritage, and family
probably loomed larger than bars or restaurants or sports or galleries, which simply did not
enjoy enough of a critical physical and experiential mass to enter as directly into the
decision-making process
Things have changed dramatically since then, as Nobel laureate economist Robert Fogel
has documented. “A century ago,” he writes, “the typical household in OECD nations
spent 80 percent of its income on food, clothing, and shelter. Today, these commodities
account for less than a third of consumption” (2000, 160). Leisure, moreover, by his
estimation rose in the United States from 18 percent of consumption in 1875 to 68 percent
in 1995 (191).
The Great Recession of 2008 narrowed options. That many recent college graduates are
choosing to move in with mom and dad rather than set out on their own is only one of its
less painful results. Still, the long-term trends seem to be broadly continuing. In the United
States, for instance, as figure 1.3 shows, the hospitality and leisure sector was one of the
first to return to its prerecession employment levels, and has been on a steady upward
trend as a share of the total labor force since the 1940s.
Figure 1.3
This figure shows the percentage of the US labor force employed in the hospitality and leisure sector from 1939 to 2015
and its arts, entertainment, and recreation subsector from 1990 to 2015 (data for the latter are not available before 1990).
Despite the general 2008 recession, there was no substantial slowing in the growth of hospitality and leisure jobs as a
share of the total workforce. Source: US Bureau of Labor Statistics (2015).
The arts, entertainment, and recreation segment of this sector has also shown steady
growth (with especially strong gains in the 1990s), and was back to its prerecession level
by early 2013. The number of personal trainers grew rapidly in the 2000s. After analyzing
trends in the cultural economy through the 2000s, Carl Grodach and Michael Seman
conclude, “At the national level, the cultural economy has not experienced a major decline
or reorganization during recession. In fact, from 2006–2009, cultural sector employment
has only nominally decreased nationally (−.35%) and the [30 metro] regions we study
experienced a slight gain (1.2%). Similarly, the basic geography of the cultural economy
remains unaffected.” And their examination of artists in particular reveals a similar
pattern: “Nationally, artists appear unaffected by the economic downturn with their slow,
steady growth in absolute numbers from 2006 to 2009” (2013, 24).
These trends confirm what observers of postindustrial societies like Daniel Bell, Gary
Becker, and Edward Glaeser have long held: that the postindustrial transition increasingly
places education, personal relations, and amenities at the center of life, for both producers
and consumers. More jobs involve, in Bell’s (1973) memorable terms, not a “game against
nature or machines” but rather a “game with other people.” A honed sensitivity to what
those other people enjoy and value becomes increasingly prized; work itself begins (for
many) to approximate a lifestyle decision about how to meaningfully spend one’s day
rather than necessary toil until the weekend. More consumption involves choices among
products and services differentiated by styles, designs, and personal and aesthetic
meaning, from fashion to iPods to coffee to movies. The fortunes of more cities become
more defined by how they concentrate, as Glaeser puts it, not the means of production
(e.g., factories and warehouses) but rather the means of consumption (e.g., restaurants and
nightclubs), which, like personal services, are difficult to outsource abroad or economize
through labor-saving measures like standardization or automation. Indeed, retail trade
among health and personal care stores was barely affected by the Great Recession.
This lifestyle shift toward specific consumption concerns implies that when thinking
about where to move, or why to stay, for a larger percentage of the population than
perhaps ever before, the character and style of a city’s or neighborhood’s amenities matter.
To test this, ask a group of recent or soon-to-be college graduates how many would choose
an $80,000 per year job in Peoria versus a $50,000 per year job in Chicago. Many will
choose Chicago, suggesting that the economic “amenity value” of access to Chicago’s
scenes is as much as $30,000.
But scenes matter not only for the young and the affluent. Some important sociological
research shows that many low-income African American neighborhoods have
considerable concentrations of local amenities, which endow the neighborhood with value
that cannot be measured by income alone.1 Similarly, retirees increasingly choose
downtown condominiums for the distinct style of life they afford: easy access to the opera,
restaurants, charming waterfronts, and more. Later chapters detail such patterns.
Further, sometimes unintended, consequences begin to accumulate around these sorts of
scene-driven residential decisions. This is because all sorts of characteristics may be
strongly correlated with people’s tastes for various scenes. For instance, if people from a
certain ethnic background, or with certain political attitudes, enjoy certain types of scenes,
they will tend to sort themselves into ethnic or political residential enclaves. And with
little direct intent: they more consciously focus on locating in the neighborhood with the
interesting Thai restaurants and yoga studios or near the golf course, NASCAR track, or
soccer field. The result is what journalist Bill Bishop (2008) calls “the Big Sort.” Likeminded people cluster near one another and begin to live increasingly bubbled lives,
echoing back to themselves their prejudices and predispositions. Without a basis in
personal interactions or common activities, the “other”—political, religious, ethnic—can
be reduced to caricature and stereotype.
But this type of echo-chamber effect is not the only possibility. Some types of scenes
cut across lines of education, age, politics, or race, reshuffling historic patterns of
residential segregation in the process. These often have activist organizations that
encourage participants to reach across seemingly hard-and-fast cleavages. Asian-style
martial arts clubs, as we explore later, are a prime example of organizations that “bridge”
across racial and educational differences, as are some churches and arts organizations.
And popular culture is in many ways a contemporary lingua franca. The central point is
that, whether we are talking about reinforcing or reshuffling classical social boundaries,
scenes have become potent forces in defining the composition of our residential
communities. These residential effects of scenes are the topic of chapter 5.
Box 1.4 Teaching Urbanism to New Downtown Residents
Kyle Ezell, an urban planner in Columbus, Ohio, has . . . developed a course for suburban empty nesters
and retirees that not only teaches how to pick a city retirement destination, but also the finer points of such
urban needs as . . . how to tool around on a motor scooter. . . . He has also written a guide, “Retire
Downtown: The Lifestyle Destination for Active Retirees and Empty Nesters.” . . .
He will consult with cities and developers on making downtowns more residentially friendly. He also
will host a series of parties around the country to promote the “ruppie” lifestyle this fall. . . . “Ruppie” is
Ezell’s coinage for “retired urban people.”
“Ruppies are different from yuppies, because they aren’t fixated on material things,” he said. “They want
to help, to be part of the community and be creative and keep revitalized.”
Whatever they are called, their numbers are potentially huge, as the nation’s Baby Boomers face
retirement en masse, apparently with a desire for a new place to live and substantial funds to pay for it. “I
think that all of the businesses, all the cultural institutions, everybody is trying to figure out what this
emerging demographic is all about,” says Ty Tabing, executive director of the Chicago Loop Alliance. The
civic group is sponsoring one of Ezell’s “ruppie parties.” . . .
“People who have been scared to death of urban environments can talk to people who are into it
already,” he said. “The ruppies are going to tell their stories here, how their lives have changed.”
Paul Dravillas likes the show and tell idea. He and his wife, Patricia, navigated a learning curve after
they sold their Orland Park home two years ago and bought a South Loop condo. CTA buses, in particular,
were a curiosity after a lifetime of owning two cars.
“Getting rid of one car was difficult,” says Dravillas, 69, who spent his childhood on the South Side. But
he says they don’t miss that second car; he’s happy to whip out his senior citizen bus pass for almost daily
trips on the No. 3 bus. “I did hear ‘Are you crazy?’ from my friends a little bit—no, make that a lot when
we announced we were moving to the city,” he says with a laugh. “But we love being back in the city. We
do so many more things now—Millennium Park, the Cultural Center, sailing from Burnham Harbor, than
we ever would have done if we had been driving back and forth from the suburbs.”
— Mary Umberger, “Helping Cities Lure More ‘Ruppies’” (2006)
Their economic effects are just as profound. Scenes, at least some of them, can serve as
laboratories of consumption. By way of comparison, think first of the great IBM or Bell
research labs, especially in their midcentury heyday. These were laboratories of
production, devoted to pure experimentation with an eye to new types of products, like
computers or transistors. Many of these had no direct commercial payoff, and some of
those that did only did so later, and not directly for IBM or Bell. But the results were
transformative, yielding innovations in data search algorithms, laser eye surgery, bar
codes, wireless Internet, and much, much more.
Scenes—particularly those with more alternative, expressive, transgressive, and
glamorous dimensions—also provide key stimuli for economic innovation. Elizabeth
Currid’s ethnography of New York City restaurants, bars, and nightclubs showed how
fashion designers, popular musicians, and avant-garde artists would dance and drink, rub
shoulders, observe one another’s latest aesthetic ventures on the dance floor, and
sometimes take home new ideas and inspirations. Richard Lloyd’s ethnography of
Chicago’s hip Wicker Park documented how the neighborhood scene figured into the
broader chain of cultural production, providing, among other things, a standing reserve of
coolness and buzz that could be drawn on by the likes of software designers or restaurant
entrepreneurs. The point—clear and simple to firms like Apple or Facebook—is that the
tone, the mood, the color scheme, and the sounds that come with using a product can be
just as economically decisive to its success as the script beneath it. These aesthetic
qualities do not come from nowhere. They are refined and honed through life in scenes—
on the dance floor, the catwalk, the promenade, at the racetrack, the concert hall, the
gallery opening—which in turn provide the stylistic material that designers can streamline
and package.
Even finance reporters have learned to discuss design issues explicitly in evaluating
new products and companies. This marks a sea change for those schooled in the dreary
science of economic theory, past tense. Gary Becker wrote about buzz, as do we; Sherwin
Rosen in “The Economics of Super Stars” pondered topics like the Beatles or Oprah
Winfrey.
Box 1.5
[Berlin’s Café de Westens is] . . . a school and a very good one at that. We learned to see there, to perceive
and to think. We learned, almost in a more penetrating way than at the university, that we were not the only
fish in the sea, and that one should not look at only one side of a thing but at least at four.
— A regular describing one of Berlin’s main prewar bohemian hangouts, quoted in Elizabeth Wilson,
Bohemians (2000, 35)
To be sure, aesthetics and the expressive are as new as Aristotle, but their democratic
scope and economic and social reverberations reach far deeper and wider than ever before.
Indeed, they can create whole new economic sectors and classes of work. Before
Starbucks, cafe culture in America was restricted to a handful of neighborhoods in college
towns like Berkeley or Cambridge, or a few grungy neighborhoods in Seattle. “No
Loitering” signs were the norm.
Now the US coffee shop industry includes about 20,000 locations. These generate
combined revenue of around $10 billion. You can get a decent cappuccino in any suburb,
and the barista is a recognizable social type. And while Starbucks’ initial expansion put
some indie coffee shops out of business, the net effect has been an increase in small and
offbeat cafes as more Americans have cultivated a taste not only for fancy caffeinated
drinks but also for hanging out, chatting, reading the paper, and working in a cafe setting
—all of which was formerly more or less the province of artists and intellectuals. In a
similar way, the iPod taught a generation to appreciate the power of aesthetic design.
These innovations generate new needs, new demands, and with them, new products, new
jobs, and new industries.
Scenes provide key resource bases for contemporary workplaces, in much the same way
that fertile soil, good sun, and clean air provide crucial resources for the farmer, and
assembly lines and oil do for the industrialist. This economic salience implies profound
transformations in theories of economic growth. Documenting and working through these
transformations is the topic of chapter 4.
Box 1.6 Japan Leader Is Poll Victim after Fashion Faux Pas
Throughout history, the shortcomings of political leaders have been a depressing litany: corruption in
office, sex scandals, verbal gaffes and the like. But it’s rare for a politician to fall out of favor over fashion
sense (or lack thereof).
Yet that seems to be the fate that history has singled out for Japanese Prime Minister Yukio Hatoyama.
True, the beleaguered leader was already struggling in the polls, but his popularity has taken a nose dive
since his appearance in public wearing a shirt that one U.S. fashion blogger described as “an item last seen
whooping it up on the Arsenio Hall show.”
Hatoyama wore the multicolored monstrosity to a recent barbecue with voters. As CNN reports, the
event was a tragically misguided effort on Hatoyama’s part to connect with the ordinary voter. His approval
rating has dropped 9 points since.
Japanese fashion critic Don Konishi told CNN that the fashion misfire shows that Hatoyama is way out
of touch with the lives of everyday citizens. (Konishi also notes this isn’t Hatoyama’s first fashion offense
—he once wore a pink blazer over a shirt emblazoned with hearts. You can see it in a Huffington Post slide
show of Hatoyama fashion.)
“This shirt comes from the ’80s or ’90s,” said Konishi. “His ideas and philosophy are old. Japan is
facing a crisis, and we can’t overcome it with a prime minister like this. A fashion designer like me can
wear this, but not the leader of Japan.” In another interview, Konishi wondered, “Is anyone able to stop him
wearing such a thing?”
— Yahoo News (May 13, 2010)
The effects of scenes go beyond residential and economic decisions, however; they
extend into politics. We have already seen a hint at one way this can occur: indirectly,
through residential sorting along party affiliation. Indeed, Bishop suggests that as lifestyle
preferences sort neighborhoods by political party, polarization increases, mutual
understanding decreases, and politics becomes a shouting match designed less to persuade
than to induce submission. Insofar as scenes contribute to this sort of residential sorting,
they may indeed be at the root of some profound changes in our political culture.
Box 1.7 A Tale of Two Cafes
Crown Point, Indiana—“Most coffeehouses seem to be more of a wasteland of people who sit and listen to
their iPods and look for their next friend in My-Space” (Cebrzynski 2008) says Dave Beckham, owner of
the Conservative Cafe. Tired of the liberal “Starbucks mode,” Beckham decided in 2008 to turn his moral
thinking into a business, and thus was born the Conservative Cafe. With the television tuned to Fox and
books by Ann Coulter lining the walls, Beckham has designed his business with two goals: good coffee and
a political bent. The cafe serves Conservative Blend, its Radical Right Blend, its Moderate Blend; left
wingers can try Liberal Blend (decaf, presumably). Beckham insists that he doesn’t stand at the door
haranguing customers with “radical ideas,” but rather just advocates the “good, old American values that
kept this country the greatest country the world has ever seen” (Cebrzynski 2008).
Poland, New York—The Revolution Cafe is a youth-led coffeehouse with a diverse and creative
atmosphere promoting local and global community. Spearheaded by adult mentor Jay Starr, the cafe is
organized and operated by local high school students in an effort to revitalize the rural area of upstate New
York. Overtly embracing community and liberal values, the Revolution Cafe shows art, hosts
performances, and works to integrate its members into the fabric of the city’s life.
— Meghan Kallman
But there are other, more direct, ways that scenes influence politics. The most central
line is that matters of aesthetics, culture, lifestyle, and consumption have themselves
become political issues in their own right, alongside classical political wedges like class or
ethnicity. Nationally, this is evident from the 1980s culture wars to the rise of the Moral
Majority in the 1990s, from the environmental to the gay marriage movements. We see
this reflected also in the personal style of political leaders. No more stuffy suits; instead
Bill Clinton plays the saxophone, George W. Bush bails hay, and Barack Obama shoots
hoops with NBA stars.
Scene-fueled politics can also transpire at the local level, often in neighborhood and city
battles over what type of scene citizens want to live in. Historian Stephen Sawyer (2012)
documented one dramatic case. A Parisian arts group, Les Frigos, fought—more or less
successfully—against impending development in its east Paris, historically working-class
neighborhood, to maintain aesthetically fitting sight lines to the Seine, among other things.
These sorts of conflicts do not occur only in Paris, however. In Chicago’s African
American Bronzeville neighborhood, people fight over closing liquor stores, whether
nightclubs are too conspicuous, and gospel versus hip-hop and house music. Films like
The Battle for Brooklyn, novels like Telegraph Avenue, and television shows like Treme
explore the tensions and complexities at stake in struggles over the cultural character of
distinctive neighborhoods undergoing rapid change.
All of this suggests we need a more culturally complex approach to understanding
political matters like polarization, voting, or movement activism. It is not enough to know
whether somebody, or a neighborhood, or a city, is rich or poor, business or union, Irish or
WASP, to determine how they will vote and what they might be fighting over. In addition
to these sorts of concerns, we will want to know if they enjoy swingers clubs, hunting
clubs, or country clubs, poetry groups or Bible groups, rap or gospel, organic grocers or
Walmarts, nightclubs or church picnics, or all of the above. Battles over multiple
consumption and lifestyle concerns—age-old ones like honor and turf, community and
neighborhood, sacred and profane, and newer ones as well—need to be considered
alongside desires for low taxes and other classical political issues. Chapter 6 shows just
how strongly scene differences correlate with political differences, both in voting and in
new social movement activity.
Where Everyday Knowledge Ends, Social Science Begins
None of what has been said so far requires much by way of specialized knowledge to
grasp. These processes are intuitively accessible and familiar in our everyday lives.
Yet our everyday knowledge of scenes does run up against certain limits. We all live
mostly in a few scenes with which we are intimately familiar. This makes it hard to
acquire the comparative knowledge necessary to determine what, in fact, is truly unique,
or truly common, about them. You may even know where every movie theater, art gallery,
bowling alley, skating rink, and underground rave club in your neighborhood or city is
located. But almost nobody knows how his or her local set of options compares to what
other places have—not only whether somewhere else has more or less of the same things,
but also whether it has different types, or perhaps the same ones, in different
combinations, producing different overall scenes.
Some of us may travel more than others. But who can claim to have visited the tens of
thousands of neighborhoods in countries as large and diverse as the United States or
Canada, and beyond? And to remember everything in each? By allowing us to gather and
classify data on hundreds of types of amenities for these local-level units, the tools of
social science can in effect permit us to travel to all these places without leaving our
computer screens.
Moreover, it is hard to assess the real effects of scenes just by looking at the ones
around us. Suppose you see all sorts of new businesses opening in your local arts and
entertainment district. Is this because of the scene? Or is it because the people who live in
that district have college degrees, and wherever there are college graduates, there tends to
be growth? Or maybe both in combination?
With just a few cases, we cannot say. But with, as social scientists say, a large N
(number of cases), we can go beyond the specific case and ask, Is it the case that, among
places with roughly similar average educational levels, changing the scene—adding some
art galleries or Thai restaurants or secondhand boutiques—brings with it new business
activity, rising rents, rising incomes? Or are these economic variables constant across
variations in scenes but correlated with changes in education? If the former, then we have
reason to believe that scenes do in fact generate “independent” economic effects; if the
latter, that hypothesis is weakened. This is an example of the sort of “multivariate”
analysis that populates later chapters.
For now, let us focus squarely on the question of what a social science perspective can
add to our everyday understanding of scenes. Two metaphors from other scientific
domains help us to see this: molecules and fruit flies.
Molecular Aesthetics, or Toward a Periodic Table of Cultural Elements
Take two hydrogen atoms and one oxygen atom. Everybody knows what you get: water.
Throw some carbon atoms into the mix, and you might get something else, carbon
dioxide.
Hydrogen can be studied in its own right, as can oxygen and carbon. Though they may
have certain tendencies to combine in certain ways, there is nothing that logically or
metaphysically determines how they should do so, or even if they will do so in the first
place. But when, or if, they do, something new emerges, like water or carbon dioxide. And
these complexes of atoms—molecules—have their own properties not “in” any of their
elements. Water is wet and you can drink it. Carbon dioxide can extinguish electrical fires.
The periodic table of elements organizes nature’s various atomic elements into rows and
columns based on their properties, such as their atomic number or how metallic they are.
Starting with these elements, we can see the various ways in which atoms may combine
into molecular compounds. While this is all obvious enough today, the idea that there
might be a relatively manageable set of elements and, more radically, that the water we
drink and the air we breathe might be made up of various configurations of these same
elements, took centuries to develop. The simple and clear periodic table on your high
school science class window, that is to say, the outcome of hundreds of years of scientific
debate and discovery, is much messier than we are often led to believe, and is still a matter
of dispute to this day. Eric Scerri (2006) has documented much of this history in his The
Periodic Table: Its Story and Its Significance.
Now think about what a periodic table of cultural elements might look like. It would
start not with alkalis and noble gases but with discrete bits of aesthetic meaning, like
tradition, or neighborliness, or transgression, or glamour, or formality. Each of these—
tradition or transgression—could be, and would have to be, elaborated independently, in
its own right, just as we study oxygen and hydrogen on their own. This would mean
articulating what we might call “the world picture” implied by the cultural element in
question: the way a traditional aesthetic links you back to the past, bringing the weight of
millennia to bear on the present; the way a transgressive aesthetic shatters existing
conventions, finding joy in breaking the mold.
Like natural elements, cultural elements are not bound by logic or metaphysics to
combine in any particular ways. Though there are tendencies: tradition may be more likely
to join with neighborliness, transgression with self-expression. But just as the lab, or
specific geological processes, can make all sorts of alternative chemical combinations, so
can cultural elements be combined in numerous ways in different historical and
geographic situations. And when they do, different complexes emerge—not molecules,
but scenes.
To push the metaphor further, consider one cultural element, or as we call it later, scene
dimension: self-expression. This is an aesthetic that prizes improvisation, spontaneity, in a
way that expresses your own unique perspective, as in a jazz solo or improv comedy bit. If
we combine this with transgression, we would get something approaching a Bohemian
scene, in the Parisian mode, and the poetry of Baudelaire would be our guide. If instead
we combined self-expression with, say, local authenticity, we might produce a different
compound, something more like a Carmel, California, with landscape painting galleries,
bed and breakfast inns, distinctive sunsets, and the Monterey Jazz Festival nearby; the
operas of Rossini might be our model of the scene. Joining self-expression with glamour
would produce something else again, more Hollywood and less Greenwich Village.
Renoir’s great painting La Loge could embody the aesthetic of this scene. These
combinations have a life of their own above and beyond the elements that compose them,
just as water does vis-à-vis hydrogen and oxygen.
Chapter 2 works through 15 of these cultural elements, or scenes dimensions, in detail,
and provides some examples of how they can be combined into larger complexes, which
we call by names like Bohemia, LA-LA Land, Rossini’s Tour, and Disney Heaven.
The power of this approach should be evident. Just as the molecular revolution in
chemistry allows us to see different entities as combinations of the same elements, we can
now see different scenes as combinations of common underlying elements. Here, we find
more people attending art galleries and fusion restaurants (more self-expression) and less
community theater and gardening (less neighborliness); over there, we find the opposite. A
matrix for determining subtle similarities and differences in aesthetic meaning across
many neighborhoods and communities emerges, and the many patterns of cultural
organization across and within whole countries can be mapped, compared, analyzed.
Zip Codes Are Social Science Fruit Flies, or 40,000 Experiments in Living
Suppose you want to know what happens when an organism’s genetic code is slightly
altered. Does this change its resistance to certain diseases, arouse greater sexual activity,
produce heightened levels of aggression, or lead to some other unforeseen outcome? If
there is evidence of this change in the fossil record, that could be helpful in finding an
answer. But if the change is more recent, you might have to wait a few hundred millennia
to see its effects take their course.
That is, if you only observe long-lived animals like elephants or turtles. But if there
were an organism with a relatively simple genetic code that undergoes rapid generational
turnover, you might be able to speed up the process. Hence the fruit fly became the
evolutionary biologist’s best friend.
The technique is of course familiar. You take two basically identical clutches of fruit
flies and induce some slight genetic modification in the second but not the first. Then put
them in two separate containers. Let the biological wheels turn for a few months; several
generations pass. Then you see if the two clutches have evolved in different ways.
Even if there is no literal social equivalent to the fruit fly, it provides a useful metaphor
that suggests we look to smaller units of analysis, such as the US zip code. There are over
40,000 of them, each with its own internal structure and code, their boundaries remain
relatively stable over time, and they cover the entire country’s geography—in contrast to
census tracts, which are restricted to metropolitan areas. The US Census Bureau collects
information about zip codes, such as the total number of college graduates, people who
claim Irish ancestry, others who claim “American,” 25- to 34-year-olds, not to mention
income, population density, and more. And each year it also collects zip code information
about the total number of businesses and their employees. It uses a classification system
called the North American Industrial Classification System (NAICS), which includes all
sorts of useful indicators of local variation in scenes, like religious organizations, art
galleries, musicians, environmental organizations, and much more.
In addition to these government sources, there are also the yellow pages. They are now
digitized and available online. You can download them, and we did: hundreds of different
categories, scores of restaurant types, dozens of types of churches, hunting and fishing
lodges, body art and piercing studios, used record stores, ice cream shops, parks and
playgrounds, cemeteries, and more.
If you put all this information together, even allowing for some vagaries in
categorization protocols, you know a lot about the people and activities that characterize
each zip code. And you can use this aggregated information to get a remarkably clear read
on the aesthetic qualities of any given place. Other sources can provide useful
supplements, like surveys of individuals (but these rarely go below the county level) or
specialized directories (of, for instance, theaters or genealogy societies), and we have
explored many of these. These sources, different from most past social science research in
this amount of zip code depth (rather than states or counties) and precision (there are
thousands of categories we can classify), provide grist for some fairly subtle aesthetic
distinctions if one measures and mixes them thoughtfully, as chapter 3, our quantitative
tour of the US “scenescape,” makes clear.
Having this amount of information, down to such small units, makes a huge social
scientific difference. By way of comparison, there are about 3,000 counties, about 340
metropolitan areas, and, of course, 50 states. Most social science studies do their analyses
at these higher levels, with the sociological equivalent of elephant herds, which leaves
most on-the-ground processes obscurely lumped together, with not enough variation to see
meaningful differences. The “big data” revolution is more about such range, diversity, and
combinations of indicators than sheer numbers—although large numbers are foundational
as well.
Having more cases has the simple but critical benefit of permitting all sorts of statistical
analyses otherwise impossible, or at least uninformative. With a large N, you can do the
sort of multivariate analysis we noted above, “controlling” or “accounting” for a host of
other variables that might otherwise explain what you think the scene might be doing. We
typically account for a “core” set of variables in our analyses: population, income,
education, rent, race, crime, and some other, more unusual variables, such as the
concentration of arts jobs, and whether the scene is more communitarian or urbane (as we
describe in more detail later). For some specific questions we add others.
The social scientific value of the zip code fruit fly is more than statistical, however; it is
substantive. For each zip code embodies a kind of experiment in living. We are observing
thousands of experiments in living. Here, people are trying out a more transgressive and
self-expressive way of living; there, others are trying out a more traditional way; over
here, others are experimenting with local authenticity; over there, others are giving the
corporate brand a go as a source of personal meaning; and other places combine all the
above.
How do these experiments turn out? With so many observations, we have enough
variation to find out. Does a little bit more transgression relative to tradition generate a
greater or lesser influx of college graduates? At what point does more local authenticity
translate into more baby boomers? What happens if it is mixed with a bit of selfexpression? Do yoga studios, evangelical churches, or martial arts clubs do a better job of
appealing across ethnic lines? Do tech firms immersed in scenes that encourage personal
self-expression do better than similar firms that are not? The zip code fruit fly makes these
into answerable questions. Later chapters indeed answer them. Figure 1.4 illustrates our
typical analytical approach.
Figure 1.4
An interactive approach to scenes analysis: how a self-expressive scene enhances the impact of technology clusters on
the local economy. This figure illustrates the following: (1) The multicausal approach developed in later chapters of
joining tech clusters and self-expressive scenes, and eight other core variables (rent, education, race, artist clusters,
population, crime rates, party voting, and Urbane/Communitarian scenes), not displayed. The direct effects of both
follow two paths, extending from the self-expression and tech cluster boxes, respectively. (2) The third path leads into
the circle. It designates the interaction or mediated effect, which occurs when tech clusters combine with self-expressive
scenes.
It would be a mistake, however, to assume that zip codes are independent of one
another. Two very similar scenes in different contexts, near different zip codes, may have
very different meanings. And again, with so many cases, we can investigate how a scene
in one zip code relates to those in surrounding zip codes. For instance, a strongly
countercultural Bohemian scene may stand out sharply when it is in decidedly unBohemian surroundings, that is, when the zip codes around it are not very Bohemian but
are rather traditional. An “equally” countercultural scene may in fact be experienced quite
differently when “everybody else” nearby accepts, or at least tolerates, Bohemianism, that
is, when the surrounding zip codes are more transgressive.
And this too suggests a kind of hypothesis, which we can test. Measure all counties in
the country based on how traditional they are on average, scene-wise, aesthetically, in
terms of their styles of life. Then examine zip codes within these counties, and see how
the zip codes shift if their counties are more or less traditional. Do higher levels of
Bohemianism lead to the same outcomes regardless of the surrounding scene? But if in the
more traditional counties, stronger Bohemianism translates into, say, even stronger
population and income gains, then the contextual contrast makes a clear difference.
Chapter 4 documents this experiment and shows that yes, Bohemia’s allure is heightened
where it contrasts with its surroundings.
This is a book about scenes. What they are, where they are, why they matter. This first
chapter sets the scene for the rest, introducing the style of thinking and types of analyses
that come in what follows. Chapter 2, “A Theory of Scenes,” moves through our 15
dimensions of scenes and the world pictures they suggest, and shows how to combine
them into various complex wholes. Chapter 3, “Quantitative Flânerie,” takes a tour around
the “scenescape,” showing how much aesthetic variation it holds, and illustrating in the
process how we translate the raw, cold bits of yellow pages and census data into measures
of the heart, the spirit, the scene, of a place.
Chapters 4, 5, and 6 are the analytical core of the book. They analyze how variations in
scenes relate to other important social domains. Chapter 4, “Back to the Land, On to the
Scene,” investigates how scenes contribute to economic growth and prosperity, linking
scenes to the classical concept of “land.” The idea is that the economic potential of scenes
can be understood as an extension of “land” as a factor of production, connected to the
classical “land, labor, and capital” model from Smith to Ricardo to Marx and then revised
by Weber, Marshall, and Parsons. Building on this idea, we propose and test several
hypotheses about the economic impact of scenes: for instance, that glamour and selfexpression are key drivers of growth; that Bohemian scenes in communitarian
surroundings are linked with growth, while Bohemian scenes in urbane surroundings are
not; that walkability enhances the impact of local authenticity; and that local authenticity
can compensate for relatively limited natural amenities.
Chapter 5, “Home, Home on the Scene,” examines which types of residents live in
which types of scenes. The chapter is organized around a discussion of the Chicago
School of urban sociology and how a focus on neighborhoods combined with the scenes
approach constitutes part of a “New Chicago School.” The chapter includes two major
analytical sections. One, “Home Is Where the Scene Is,” shows how specific
subpopulations, like age groups or artists, tend to live in different scenes, drawing out the
implications of these patterns for how American communities may be changing. The
other, “A Great Divide?,” shows that American communities are both separated and linked
by scenes. The picture of American neighborhoods that emerges is more crosscutting and
pluralistic than standard and popular narratives stressing hard-and-fast divisions, fractures,
and cleavages suggest.
Chapter 6, “Scene Power,” turns to politics. The chapter shows how voting and other
political activities vary considerably by local context. It has three major sections. The first
lays out general processes deepening the integration of scenes and politics, and elaborates
a theory of how scenes produce key resources, which we term “buzz,” that can be used to
wield influence and acquire other important resources, such as money, power, and trust.
We illustrate these resource dynamics with the case of local political controversies in
Toronto. The second section turns to a broader comparative perspective, examining the
types of neighborhoods in which new social movement (NSM) organizations thrive.
Despite their universalistic claims, such organizations are more numerous, the chapter
shows, in places similar to the ones in which Jane Jacobs lived: educated, dense, walkable,
full of artists and self-expressive scenes. Outside of such neighborhoods, NSM
organizations are relatively rare. Third, we turn to national politics. We demonstrate that
correlations between scenes and presidential voting patterns have increased in recent
decades and show that such correlations are not reducible to other important variables. At
the same time we point toward interactions between scenes and other factors, specifically
that the political implications of affluence (measured as high average rents) shift in more
versus less transgressive scenes. This we interpret, drawing on David Brooks (2000), as a
“Bobo” effect. All told the chapter points toward an account of politics that stresses its
contextual and local cultural contingencies rather than the clear reds and blues of the
standard media map.
Policy is the theme of chapter 7, “Making a Scene.” The target audience here is local
and national policy makers. The chapter provides a general overview of how the idea of
scenes fits into broader urban and community policy challenges, before turning to specific
advice about how to integrate scene ideas into such policy. We illustrate with examples of
cases where scenes have been key policy levers, featuring our own policy experiences in
Toronto and Chicago.
Chapter 8, “The Science of Scenes,” is a self-reflective discussion of methods and
concepts that takes up concerns of primary interest to professional academic readers. It
reviews the scholarly literature related to scenes, situates our concepts in reference to it,
and discusses technical issues and assumptions around data, methods, measurement, and
analysis. An extended discussion of “modeling context” shows how to apply moreadvanced statistical techniques (like adjacency analysis) to illuminate how the spatial
location of scenes shifts their dynamics. The discussion here is more technical, but again,
the goal is to convey complex ideas in a relatively intuitive style, grounded in examples.
The chapter also discusses the chicken-and-egg problem of causality in scenes analysis
(and more broadly), illustrated with an analysis of how the relationship between arts jobs
and total jobs shifts over time; includes a discussion of how to treat scenes as outcomes
and not only as drivers of social processes (which the book typically does); and reviews
ongoing work on scenes internationally.
Throughout this book we touch on a number of issues of substantive and contemporary
importance, such as drivers of economic growth, community composition, and political
cleavages. Yet time marches on, and new issues emerge, just as new data sources
constantly become available. Most of the data in this book come from the 1990 and 2000
censuses, plus online yellow pages directories downloaded in the mid-2000s. The 2010
census was not available at the time of writing, and new “big data” possibilities are
emerging every day. These hold great potential, and we are exploring them presently.
While new sources and hot topics offer considerable interest, the main goal of the book
goes beyond them: not to get the latest news but to elaborate how to make and understand
news in new ways.
2
A Theory of Scenes
Molecules and fruit flies offer useful metaphors from the physical sciences for thinking
about scenes. But similar issues about how to understand the relationships between wholes
and parts, different levels of analysis, contexts, and the like have been just as significant in
the social sciences, especially in their formative late nineteenth- and early twentiethcentury period. Such questions were widely discussed in the emerging human science
disciplines both on the Continent and in the New World.
No single social scientific paradigm has emerged, however, to “solve” or “synthesize”
these problems, nor does one seem to be on the horizon. But there is often a common
animating ambition: to combine the precision of the physical sciences with the sensitivity
to the depth and range of human experience characteristic of the humanities and the arts.
This chapter develops a theoretical framework for the study of scenes rooted in this
ambition.
It is a delicate balancing act. We want a framework open to a wide range of meanings,
styles, and aesthetics. But we want to be clear and specific enough to be able to measure
these meanings with a level of precision that permits us to compare them to other
important characteristics of places, such as the income or educational levels of their
residents.
The “theory of scenes” which follows is the result. What kind of theory? This book has
two types. The first asks descriptive “what is” questions. The second asks explanatory
“why is” questions. Being clear about the difference is important.
When we do descriptive theory, we are forging conceptual tools to capture some
phenomenon, in this case the character of a scene. Successful descriptive theory helps
pinpoint the core concepts. Successful methods consist in reliably measuring what we
think we are measuring—such as linking a certain type of scene to a certain place.
By contrast, when we do explanatory work, we are making a statement about what
caused something to be the way it is or what other things it makes happen. That is, we
want an account of why this type of scene came into being here and now, and of what
tends to happen if it is there. Explanatory theorizing articulates processes that lead from
cause to effect. Successful methods permit us to tease out the relative impacts of many
causes on many effects.
Explanatory theory necessarily presumes that we have adequately described and
measured the phenomenon. We presume we know what the scene is and where it is, and
we ask what follows from that. Description therefore precedes explanation. Hence this
chapter and the following one operate on the descriptive level; this chapter develops
concepts, the next methods linking the concepts to empirical data. Remaining chapters
build explanations from these two.
More specifically, the present chapter develops concepts for answering the question,
what kind of a scene is this? It comes in four sections. The first argues that any answer to
the question has to be multidimensional, that is, any specific scene is a complex of many
dimensions, like tradition, transgression, or self-expression. The second lays out a
paradigm for organizing 15 such dimensions into three major types of meaning:
authenticity, theatricality, and legitimacy. The third shows how to combine these
dimensions into complex wholes. The fourth discusses general principles of empirical
measurement that these concepts imply.
Scenes as Multidimensional Complexes
The theory of scenes critically extends some of the main traditions of cultural analysis in
the social sciences, many of which oscillate between extremes of universalism and
particularism.
On one end, “culture” suggests a single, totalizing, delimited set of values that define a
whole people or civilization: “Western culture,” “European culture,” “American culture,”
and so on. “Culture” in this sense cuts off investigation of internal variations within a
given unit of analysis (America, Europe, etc.). And it short-circuits the search for
commonalities across geographic areas—like California beaches and gardens that resonate
with those in Italy and Japan.
On the other end of the spectrum is a tendency toward a strong particularism. “Local
culture” often suggests incomparably unique snowflakes, as in case studies of Chicago’s
Bridgeport or New York’s Harlem. “Culture,” in thus relying strongly on proper names
like Harlem, can stop comparison before it starts, as it can lead so deeply into the
particular life of a particular place that the broader world of which it is a part disappears.
A keynote in recent sociology of culture has been that this dichotomy is untenable. As
John Levi Martin puts it, social categories typically vary “within cultures, not across
them” (2011, 139). That is, societies are not bounded systems that correspond one-to-one
with certain unique cultural qualities (e.g., “Americans are hardworking”).1 That any
given civilization contains, for instance, both ascriptive and universalist cultural strands—
those defined by the group you come from and those open to all—in different degrees and
concentrations, was a theme stressed especially by Schmuel Eisenstadt, who sought to
theorize globally yet retain cultural distinctiveness. In a similar way, Richard Peterson’s
studies of the “cultural omnivore” direct attention away from strict correspondences
between social and cultural distinctions, showing that many people who enjoy “highbrow”
culture like opera also enjoy “lowbrow” culture like pop music. The question then
becomes, How, when, where, and why do particular people gather around particular sets of
cultural tastes and activities, to what extent do these tastes and activities both differentiate
people by and build bridges across various social categories (like income, race, and
religion), and how does the way they do so vary by place and time?
“Scene” is a powerful conceptual tool for discerning the range and configurations of
aesthetic meanings expressed within and across various places, for seeing the clumpiness
of cultural life. For the concept of scene nicely directs our focus not at “common values”
or “ways of life” hermetically sealed from “other cultures” but rather at multiple, loosely
binding, more flexible arrays of local meanings. At the same time, in contrast to
“culture’s” equally demanding doppelganger, “subculture,” “scene” does not necessarily
imply all-embracing oppositional or underground cultures or local variants of a higherorder common culture. People can choose to enter or leave different scenes; scenes
facilitate more choices than “primordial” characteristics like race, class, national origin,
and gender. The concept is sufficiently open to include marginal as well as less
transgressive cultural styles—not “ways of life” or “conditions of life” but looser “styles
of life” make the scene.
At the same time, “scene” facilitates cross-case comparison. The concept focuses on the
range of cultural meanings expressed in and by the many activities and people that define
the lifestyle of a place, including, but not restricted to, ethnic or class labels. This focus on
style distinguishes “scene” from “milieu,” as in the “student milieu,” which says little
about the difference between frat party and vegan co-op. And because the cultural
elements of a scene—glamour, corporateness, formality, charisma, and the like—can be
found in many places, we can pinpoint the precise character of one scene versus another
by comparing how they combine these elements. A city’s cultural organization thereby
emerges as something that can be mapped and analyzed.
Three Scenes
To see how these general ideas about scenes as multidimensional wholes translate into an
analytical model, some examples may be useful. We want to answer the question, what
kind of scene is this? The examples help illustrate how to do so.
Think of three scenes. In the first, we are in a classic Chicago ethnic neighborhood. Old
men are sipping cappuccinos outside a cafe while their younger fellows play pool inside.
Nearby, shoppers sift through baskets of zucchini and peppers at an outdoor fruit and
vegetable market. An afternoon mass is letting out down the block.
Now consider a second scene, a more Neo-Bohemian one like Chicago’s Wicker Park
or Toronto’s West Queen West. In this one, young people sip coffee on an outdoor patio
while indie rock floats through the air. Laptops sit on the tables. Inside, competitors start
signing up for an impending poetry slam as an audience gathers. Restaurants nearby are
serving cuisine from around the world, and the air is filled with an unusual mix of scents
as chefs combine spices and flavors in hitherto unimagined fusions.
Now imagine a third scene, perhaps in Toronto’s Bay Street or Chicago’s Loop areas.
Professional men and women in business suits are power lunching, decked out in red ties
and high heels, pinstripes and briefcases. Smartphones flash urgently, and stock prices
scroll along the television, which is tuned to Bloomberg TV. Broadway-style marquees
begin to light up as makeup artists arrive to paint the stars for the evening. A mannequin
designer nearby is putting the finishing touches on a Saks Fifth Avenue display.
Each scene is full of different activities and experiences. And these experiences in turn
are facilitated by the availability of various amenities. Cafes, restaurants, theaters,
department stores, churches, and the like provide the venues, occasions, and even
instigations for each scene to take its shape.
It Is Hard to Say What a Scene Consists in, Explicitly
If we want to say explicitly, in more than diffuse intuitions, what makes these scenes what
they are, what their specific characters and qualities consist in, it is not easy. We cannot
look to any one type of amenity or activity. In all three, there is coffee and music, drinking
and eating, work and leisure. They all probably have some restaurants, shops, music
venues, and very likely a church. This implies that the character of the scene does not
inhere in any single amenity. We always have to look to collections, mixes, and sets to get
a read on what makes this scene different from that one.
Box 2.1 What Is an “Amenity”?
“Amenity,” drawn from economics, is a slippery term. It is related to “consumption,” typically referring to
pleasurable but unquantifiable aspects of goods and services related to their use or enjoyment; this is
contrasted to productive “capital” that increases market value. In this use of the term, operas, parks, fishing
lakes, and dance clubs are amenities. Economists have typically analyzed the impacts of natural amenities
like clean air and warm weather on rents.
But amenities also have productive market value, as authors like Pierre Bourdieu and others have
stressed in analyzing how they build cultural or symbolic capital. The same factory can be viewed as an
amenity and as a firm under different analytical lenses, the latter when we ask how much it produces, the
former when we ask whether it mars the landscape.
Including as amenities businesses and other organizations recognizes that for-profit businesses can
provide this enjoyment and market value simultaneously. Buying sushi or pizza is a market transaction, but
living in a neighborhood with easily available sushi and pizza restaurants provides a pleasure above and
beyond the market value in such transactions. People—artists, old-timers, and so on—can be amenities too,
in that others might move to, or visit, specific neighborhoods in part because of the kinds of people they
expect to find there.
To be sure, not every object is as easily or neatly regarded as an amenity. Some objects make better
subjects for scenes. Art galleries, gourmet coffee shops, gun depots, or Walmarts might reveal more
meaning than gas stations do. Decisions must therefore be made about what and how much to include in
the picture just like a director must decide what to include in the shot. Too much can muddy the waters.
Too little fails to adequately capture the activities and practices characteristic of a place. A reasonable
solution is to include a broad range of categories—from operas to advertising agencies, catfish restaurants
to legal offices—to discern the many activities and practices that define the local scene. This approach—
including a far wider range of amenities, and then assessing the meanings they take on through various
combinations—is a foundational difference between our and past work on amenities.
— The authors
Other sociologists and economists of culture have analyzed the qualitative
characteristics of localities by measuring only one type of amenity, or a few, such as
restaurants, museums, or bookstores. We build on this work and use amenities as key
indicators for measuring scenes. We go further, however, by downloading and aggregating
hundreds of different types of amenities for every zip code in the United States and postal
area in Canada. This gives a far more holistic picture, one that allows us to see how the
same amenity (e.g., a tattoo parlor) can take on different meanings when joined by others
(e.g., an art gallery or hunting lodge). Chapter 3, “Quantitative Flânerie,” gives a scenic
tour around the United States and Canada using these data. We occasionally contrast
results from parallel studies in France, Spain, Korea, Japan, China, and Poland.
Before these raw data can be meaningful, however, we need to develop some
conceptual tools for distilling the character of the scene from them. This is because not
only does no single amenity make any particular scene; each amenity contributes to the
overall scene in many different ways. The imported Italian cappuccino may evoke a sense
of local authenticity but it might also at the same time suggest the legitimacy of tradition,
doing things in the way they have been done in the past. The pan-Asian restaurant may
celebrate the importance of ethnic culture but simultaneously affirm the value in
expressing some unique, personal twist on old techniques. The nightclub red carpet VIP
area may evince glamour just as much as it demands attention to formality, adhering to
codified standards of appearance, like dress codes. Both-and, not either-or, has to be the
watchword for any theory of scenes.
Further difficulties arise when we move more deeply from amenities and activities and
people into what they mean. In so doing we necessarily move to a higher level of
abstraction. This is because the same qualities can be found in many different scenes,
expressed by many different amenities. Take local authenticity. It is there in the Italian
cafe, in the label telling you the small Sicilian village from which this particular espresso
blend is derived, and in the photos showing the local little league team it sponsors. But it
is just as much there in the pile of CDs by local bands for sale on the counter at the indie
cafe or in the subtle references to neighborhood history and landmarks during the poetry
slam that “only locals” would “get.”
Because the same dimensions of meaning can be present across scenes, their qualities
can (and must) be abstracted from any specific scene. Each quality—local authenticity,
transgression, tradition, glamour, formality—has its own character that can be articulated
separately. This also implies that no single abstract quality defines any particular scene. If
both ethnic neighborhood and Neo-Bohemian scenes have a dimension of local
authenticity, this does not make them the same. The difference lies in how this one quality
combines with others in each particular configuration—one with self-expression and
transgression, the other with neighborliness and tradition. However these combinations
emerged, the resulting scene is a specific combination of multiple traits.
Box 2.2
Instead of producing something common to all that we call language, I am saying that these phenomena
have no one thing in common which makes us use the same word for all,—but that they are related to one
another in many different ways. And it is because of this relationship, or these relationships, that we call
them all “language.” I will try to explain this. . . .
Look for example at board-games, with their multifarious relationships. Now pass to card-games; here
you find many correspondences with the first group, but many common features drop out, and others
appear. . . .
And the result of this examination is: we see a complicated network of similarities overlapping and crisscrossing: sometimes overall similarities . . .
I can think of no better expression to characterize these similarities than “family resemblances”; for the
various resemblances between members of a family: build, features, color of eyes, gait, temperament, etc.
etc. overlap and criss-cross in the same way.—And I shall say: “games” form a family.
— Ludwig Wittgenstein, Philosophical Investigations (1973, aphorisms 65–69)
The Many Meanings of a Scene
We have to rise to more abstract dimensions of meaning to answer the question, what type
of scene is this? Here again we find immediate challenges. Which dimensions should we
choose? What will be, that is, the metaphorical atoms of our periodic table of cultural
elements? How will we organize it? When will we know we are done, and how? There are
no final answers to these questions. What follows is pragmatic guidance based on
experience with these fundamental issues.
Box 2.3
The whole universe of concrete objects, as we know them, swims, not only for a transcendentalist writer
[e.g., Emerson], but for all of us, in a wider and higher universe of abstracted ideas, that lend it its
significance. As time, space, and the ether soak through all things, so (we feel) do abstract and essential
goodness, beauty, strength, significance, justice, soak though all things good, strong, significant, and just.
Such ideas, and others equally abstract, form the background for all our facts, the fountain-head of all the
possibilities we conceive of. They give its “nature,” as we call it, to every special thing. Everything we
know is “what” it is by sharing in the nature of one of these abstractions. We can never look directly at
them, for they are bodiless and featureless and footless, but we grasp all other things by their means, and in
handling the real world we should be stricken with helplessness in just so far forth as we might lose these
mental objects, these adjectives and adverbs and predicates and heads of classification and conception.
— William James, The Varieties of Religious Experience (1902, 56)
We face a dilemma right from the start. If we try to delimit ahead of time what cultural
elements can inhere in a scene, we will never be able to stop. For every five qualities we
list, you can think of five more. At the same time, we cannot “just look” at the world of
scenes and expect some fixed set of qualities to pop out. We have to know what to look
for. And, as William James says, it is in abstract qualities like beauty or strength that
things and facts appear to us at all in the first place.
The most prudent course of action seems to be to take a kind of middle road, neither
pure systematic theory nor pure empiricism. Instead, we can look to a range of sources
from the world of culture, like poetry, novels, religion, films, and also to nonfiction, like
journalism, ethnographies, surveys, case studies, social theory, aesthetic theory, cultural
theory, and philosophy.
Such sources illustrate crucial and recurrent themes that have occurred to participants in
and observers of scenes themselves. We can add subtlety by building on those critics,
philosophers, journalists, ethnographers who have spent the past few centuries trying to
describe the key aesthetic features of many scenes, even if not under the precise heading
of “scene.” While this approach might not yield a closed system, it is enough,
pragmatically, to build a workable set of dimensions that combine in a scene. No doubt,
the sorts of categories that emerge—like charisma, self-expression, or glamour—are not
the normal stuff of academic social science journals. But this is, in a way, precisely the
point: we want to take concepts familiar in social and cultural theory (like glamour and
charisma), root them in the ground, in the amenities that dot our streets and strips, and
show that such concepts can be placed alongside the likes of median gross rent or GDP.
Authenticity, Theatricality, Legitimacy
On this middle road, the goal is to gather and bring together the bounty from current and
classic cultural analysis. Yet further questions arise immediately. What types of meaning
are we going to look for? Again, an exhaustive answer seems unlikely. But some general
categories provide headings under which to gather our cultural elements.
For a start, return to the three scenes above, the ethnic neighborhood, Neo-Bohemia,
and downtown scenes. And now note that, while each “says” a lot, the kinds of things they
say have similarities. The images of small Italian villages, indie record labels, and
corporate logos all affirm or deny something about who you really are. Call this
authenticity—they are all saying something about how to be authentic. How they say this
differs—by being from a particular place and sharing local customs, by coming from a
particular ethnic heritage, by possessing a certain brand name (Gucci not knockoffs).
These meanings resemble one another in that all point to something considered genuine
rather than phony, real not fake.
But scenes say more than just how to be real. There is also something in the scene about
how to present yourself, in your clothes, speech, manners, posture, bearing, appearance. In
the checked tablecloths and family-style service of a local pizza joint, there is a suggestion
to present yourself in a warm, intimate, neighborly way; a formal way in the dress code
and sea of black suits at a power lunch venue; a transgressive way in the ripped jeans and
anarchist symbols on the wall at the Marxist cafe. Call these modes of appearance styles
of theatricality, and we have another general type of meaning a scene can support or
reject.
Authenticity is about who you really are; theatricality is about how you appear. Just as
important is what you believe makes your actions right or wrong. And scenes say
something about this, but again, in different ways. If the Catholic mass says listen to
tradition, the poetry slam MC is saying listen to yourself; if the human rights watch poster
on the wall says listen to the universal voice of humanity equally, the portraits of Che
Guevara, Steve Jobs, and Ronald Reagan are saying listen to what great leaders say. Think
of these ways of determining what is right or wrong as types of legitimacy. Thus we have
three general categories of meaning at stake in a scene—authenticity, theatricality, and
legitimacy—each of which has been a major concern in various traditions of social
thought, from Max Weber on legitimacy to Erving Goffman on theatricality to Georg
Simmel on authenticity, among others. While subtly articulating the deep meaning of these
categories and their twists and turns across various authors is a worthwhile pursuit, our
goal here is less hermeneutic and more analytical, to join them into a flexible framework
for comparing scenes. Table 2.1 summarizes key characteristics of authenticity,
theatricality, and legitimacy.
Table 2.1. Analytical components of scenes I: Theatricality, authenticity, legitimacy
Theatricality
Authenticity
Legitimacy
Mutual self-display
Discovering the real thing
Acting on moral bases
Seeing and being seen
Touching ground
Listening to duty
Appropriate vs. inappropriate
Genuine vs. phony
Right vs. wrong
Appearance
Identity
Intentions to act
Performing
Rooting
Evaluating
Box 2.4
Figure 2.1
This figure is a Google Ngram. It shows changes in average usage of the term “authenticity” in books from
1700 to 2000.
The search for authenticity has a powerful hold over the contemporary imagination. Stemming from the
Greek words for “by my own hand,” the modern terms “authentic” and “authenticity” emerged in the
fourteenth and eighteenth century, respectively. The words gained symbolic force in the hands of writers
like Kierkegaard and Heidegger, who built on traditions running back at least to Rousseau, Goethe,
Schiller, and Wordsworth. The value-charge loaded into the terms responds to a perceived problem
endemic to modernity. As Marx famously put it, “All that is solid melts into air.”
Usage rose at the time of the French Revolution, declined from the 1830s to the 1920s, but steadily
increased up to the 1980s. Then it rose to new heights from the 1980s into the first decade of the twentyfirst century. Think of related phenomena such as organic food, reality TV shows, call-in talk shows, less
formal and uniform clothing.
Earlier conceptualizations thus took on a new salience. Faced with the pervasive experience of
contingency—or what many critics label manipulated, fake, ersatz experience—with the multiplicity of
lives passing this way and that through the urban crowd, on the TV screen, in the travel advertisement, with
the massive constructions of modern engineering and planning, “authenticity” emerged as a powerful
source of meaning. It offers something organic rather than artificial, seemingly unadulterated by external
intervention. Nature’s purity rather than the distortions of civilization provided one of its first and most
potent symbols. But other more social sources of the self have proven equally powerful, from untarnished
locale to primordial ethnicity to corporate brand to national state.
Google has digitalized contents of major libraries around the world, and summarized their contents so
that individual words can be tabulated, as in this figure. The exact numbers of books and titles thus vary by
period in ways that reflect progressive digitalization of content. Sampling and measurement issues of
Google books have been analyzed in several web reports by Google and others. Data were tabulated around
March 2013 using the Google Books Ngram Viewer (http://books.google.com/ngrams). The extensiveness
of the Google book database made it the most appealing that we could find at the time of our research.
To be sure, some lines between these general categories are fuzzy. Still, the differences
are real, and we can recognize them relatively easily—especially when they clash. For
instance, “being real” and “being right” can point in different directions. The charmingly
authentic Italian cappuccino shop may use coffee beans harvested under exploitative
conditions. The intellectually sincere person, in staying true to his real self, may violate
the moral expectations of his fathers.
Theatricality can clash with authenticity as well. As a form of theatricality, flashy
clothes may provide the allure of glamour; as a form of authenticity, they may reek of the
poseur. Formal gowns can make an event into an occasion just as much as they can
indicate a moral failure to think for oneself. While authenticity, theatricality, and
legitimacy need not clash, they do point at different types of criteria for evaluating the
nature of the scene.
Box 2.5 The Space of Fashion
[The space of fashion] is like the economy, where a host of individual actions concatenate. But it is
different from this as well, because our actions relate in the space of fashion in a particular way. I wear my
own kind of hat, but in doing so I am displaying my style to all of you, and in this, I am responding to your
self-display even as you will respond to mine. The space of fashion is one in which we sustain a language
together of signs and meanings, a language that is constantly changing but that is at any moment the
background needed to give our gestures the sense they have. If my hat can express my particular kind of
cocky yet understated self-display, then this is because of how the common language of style has evolved
between us up to this point. My gesture can change it, and then your responding stylistic move will take its
meaning from the new contour the language takes on.
The general structure I want to draw from this example of the space of fashion is that of a horizontal,
simultaneously mutual presence that is not of a common action but rather of mutual display. It matters to
each one of us as we act that the others are there as witness of what we are doing and thus as codeterminers of the meaning of our action.
Spaces of this kind become more and more important in modern urban society where large numbers of
people rub shoulders, unknown to each other, without dealings with each other, and yet affecting each
other, forming the inescapable context of each other’s lives.
— Charles Taylor, A Secular Age (2007, 481)
Ordering Cultural Elements
Authenticity, theatricality, and legitimacy are broad categories to help us organize the
types of meaning that a scene can support or resist. However, we need to be still more
specific. We need to be able to say what types of authenticity the scene values (or
devalues), what types of theatricality, what types of legitimacy. These specific dimensions
have been emerging already, like local authenticity, glamorous theatricality, or traditional
legitimacy. Now we are in a position to give these, and others like them—15 in all—more
substantive content, which comes in detail below.
Before that, to get a sense of how these 15 relate to one another as members of a larger
family, it helps to arrange them according to a pattern. Stretching the metaphor perhaps to
its breaking point, think of this arrangement as similar to the periodic table’s “groups” of
elements that move, generally, from more to less metallic as you move from left to right.
Even in the case of chemistry, however, “exceptions to this general rule abound” (Scerri
2006, 11). Some metals are soft and dull (like potassium and sodium) while others are
hard and shiny (like gold and platinum). The same goes for cultural elements. Rather than
treat such exceptions as thorns in our side, think of them instead as spurs to further
thought, as you or anybody else can look for new elements and new patterns. Our
international collaborators around the world are already doing this.
Consider first authenticity. Authenticity says something about the sources of your being,
where the “true you” comes from. The scope of that “you” helps to organize dimensions of
authenticity, along something like a generalizing logic. Starting at the top of the
authenticity section of table 2.2, the dimensions expand from my turf to the world. As we
move down, the narrow and particularistic authenticity of the local contra the foreign
expands outward. Getting in touch with a “real” rooted in state citizenship connects
authenticity to a translocal community, while transnational ethnic and corporate sources of
authenticity extend wider still. An ethnicity or a brand name can make a claim to
authenticity in any country. And there is in principle no limit to the scope of reason, which
can provide the true nature of not only any human, but more broadly of any rational agent,
Martians, angels, gods, whatever.
Now turn to theatricality. Theatricality is about performance, and there is a certain logic
of performance, not of specificity to generality but rather external to internal and
convention to deviance. There is first the conspicuous display of self as an object to be
viewed for the sake of being viewed: the exhibitionism of “look at me!” But what to look
at, specifically? Look down table 2.2 to see various possibilities. You can perform
according to conventional forms, formally, or by deviating from such forms,
transgressively. And you can display yourself in such a way that you direct your audience
toward your inner, intimate warmth, like a good neighbor, or toward your outer, surface
sheen, glamorously.
Table 2.2. Analytical dimensions of scenes II: 15 dimensions of theatricality,
authenticity, and legitimacy
THEATRICALITY
Exhibitionistic
Reserved
Glamorous
Ordinary
Neighborly
Distant
Transgressive
Conformist
Formal
Informal
LEGITIMACY
Traditional
Novel
Charismatic
Routine
Utilitarian
Unproductive
Egalitarian
Particularist
Self-expressive
Scripted
AUTHENTICITY
Local
Global
State
Antistate
Ethnic
Nonethnic
Corporate
Independent
Rational
Irrational
And legitimacy? Legitimacy concerns the basis of moral judgments, the authority on
which a verdict of right or wrong is grounded. Time and space are key ways of
discriminating among possible authorities. Starting from the top of the legitimacy group in
table 2.2, tradition temporally orients one toward the authority of the past—as in
classicism, which urges one to heed the wisdom of classic masters. The power of the
present inheres in the presence of a charismatic figure, in the aura of a great leader or
prophet, who says listen to me now, past and future be damned. To orient yourself toward
the authority of the future is to live not for present pleasure but rather for what is to come,
to treat the past not as a rule but as a source of information; this is the utilitarian attitude—
calculating, forward-looking, weighing alternative courses. Moving down finally to spatial
dimensions of legitimacy, there are the global ideals of egalitarianism, which says what is
good is what all can benefit from, equally (as in the moralism of fair trade coffee). And
there is the legitimacy of the individual person, where the ultimate authority resides in you
and you alone, in a unique personality revealing itself as it responds in its own way to
particular situations (the nonrepeatable uniqueness of an improvised solo or encounter).
15 Dimensions of Scenes
Just as a person can be more or less amiable or hostile, a scene may be more or less selfexpressive. And just as we get a stronger sense of what a particular person is like if we
know that she is both friendly and somewhat neurotic, we get a clearer picture of what a
specific scene is like if we know whether it joins self-expression more with transgression
than with glamour. But to make these sorts of combinations and comparisons, we need to
have a clearer sense of what glamour, or self-expression, or transgression, or the rest of the
dimensions in table 2.2 mean.
Each of these dimensions therefore needs to be articulated in more detail. Think of these
short capsule descriptions as mini “world pictures,” ways of seeing the world that can be
embodied in multiple scenes.
Theatricality
Glamour. Glamorous scenes place one in the presence of dazzling, shimmering,
mysterious but seductive personae, perfectly fashioned, like me but more than me.
Literary scholar Judith Brown describes the main elements of the experience. Glamour
raises audiences above “the multiple indignities of life on the ground” to the “coolly aloof
and beautifully coiffed” world of Hollywood fashion photography: “transfixed, one gazes
at a world of possibility that is foreclosed, inaccessible, yet endlessly alluring” (2009,
171). Planner Elizabeth Currid constructed a “geography of buzz” by counting photos
from the Getty Images archives of cultural and entertainment events: the gala exhibition or
paparazzi-surrounded nightclub far away from the unglamorous dirt and grime of
backwoods camps, greasy spoon diners, or soot-spewing factories (Currid and Williams
2010).
Neighborliness. Warm, caring members of a community joined with friends and
fellows in camaraderie—this is the ideal of neighborliness. Neighborly scenes highlight
closeness, personal networks, and the intimacy of face-to-face relations. Sociologist
Japonica Brown-Saracino found the symbolic power of neighborliness in her studies of
“social preservationists” who move into older neighborhoods and come to value the
presence of “old timers” and the styles of life they maintain. Her informants stress “the
familiarity or friendship between neighbors, the intimacy of a community . . . by
repeatedly referring to informal exchanges between neighbors, such as sharing holiday
dishes or the simple act of greeting people on the street. The presence of children and their
families is [also] important. They emphasize neighborhood parties, interactions with
strangers, community festivals, and working-class families” (2004, 145). One informant
described the attraction of Chicago’s neighborhood scenes over the Loop: “[It’s] not
neighborhoody enough there” (Brown-Saracino 2009, 90). Similarly, in Paris’s workingclass areas, past leaders regularly greeted all as “comrade.” The neighborly scene is one
where “everybody knows your name,” and this is good—the friendly local pub or
community picnic, not the crush of humanity on the crowded subway or the impersonal
calculations of the stock market.
Box 2.6
The word [glamour] originally meant a literal magic spell, which made the viewer see something that
wasn’t there. In its modern, metaphorical form, glamour usually begins with a stylized image—visual or
mental—of a person, an object, an event, or a setting. The image is not entirely false, but it is misleading.
Its allure depends on obscuring or ignoring some details while heightening others. We see the dance but not
the rehearsals, the stiletto heels but not the blisters, the skyline but not the dirty streets, the sports car but
not the gas pump. To sustain the illusion, glamour requires an element of mystery. It is not transparent or
opaque but translucent, inviting just enough familiarity to engage the imagination and trigger the viewer’s
own fantasies.
— Virginia Postrel, “A Power to Persuade” (2010)
Transgression. Transgression breaks conventional styles of appearance, shattering
normal expectations for proper comportment, dress, and manners, outraging mainstream
sensibilities. Much of what counts as transgressive will be determined by what counts as
conventional or mainstream. As sociologist Alan Blum puts it, transgression is theatrical,
and not merely doctrinal, when it involves performances and displays that break against
“the routinization of everyday life” and the rigidified confines of the self (2003, 174). The
key is to have recognized the theater of social life and to be ready to violate its scripts.
Urban ethnographer Richard Lloyd’s study of Chicago’s Wicker Park reveals how crucial
this type of theatricality is to sustaining a distinctively powerful yet fragile type of urban
ambiance, which he calls “grit as glamour.” Transgression is strong where conventional
norms of style and appearance are routinely violated—spiky hair, loudness, tattoos, and
body piercings rather than suits, button-down shirts, and “good manners.”
Box 2.7 Grit as Glamour
[For Wicker Park’s neo-bohemians,] navigating the gritty streets involved adopting an “outlaw aesthetic,”
expressed through both dress and demeanor, that was similar to the persona that Norman Mailer attributed
to the “existential hipster” during the 1950s. Such personal styles were intended to mark them as different
from mainstream society and to help them blend into the local scene as they experienced it. . . .
To be on “the edge” with all the valences that attach to this term is crucial to neo-bohemian
identification. As one West Side gallery owner put it, echoing a familiar bon mot, “If you’re not living on
the edge, you’re taking up too much space.”
— Richard Lloyd, Neo-Bohemia (2006, 83, 97)
Formality. Formal scenes prize highly ritualized, often ceremonial standards of dress,
speech, and appearance. These set one apart from humdrum routine by designating spaces
where strict canons of “good form” reign. The French novelist Stendhal was a master at
describing how much could be at stake in the way a simple gesture or phrase fits into
established patterns of social etiquette, especially in highly ritualized settings such as the
French salon. Sociologist Erving Goffman was a keen observer of this style of theatricality
at play in more modern settings, noting those “stimuli [that] tell us of the individual’s
temporary ritual state, that is, whether he is engaging in formal social activity, work, or
informal recreation” (1959, 24). The ceremonial form, conforming to the code, is key, as
in the parade before church in one’s Sunday finest, the military procession, or the closely
choreographed meal at a three-star Michelin restaurant. Informality is celebrated in the
democratic unceremoniousness of the folk music festival, the family dinner, or relaxed
bar.
Exhibitionism. Exhibitionism makes private aspects of the self highly visible
publically. The self becomes an object to be looked at, an exhibit to be admired.
Philosopher Thomas Nagel describes the exhibitionistic attitude toward sex as follows:
“The exhibitionist wishes to display his desire without needing to be desired in turn”
(2008, 40). The goal is to be aroused, to be seen as such, but without demanding, or
expecting, arousal in turn. It is a play of seeing itself, and being seen. This general attitude
goes beyond sex, narrowly understood. Think of dancers on a raised platform to be gazed
upon while gyrating before a nightclub’s heaving crowd; or Muscle Beach in Venice,
California, where bodybuilders work out not only to increase their strength but also to flex
their bare chests in view of spectators passing by; or sidewalk cafes in which intimate
conversations between two lovers become part of the urban museum. These are forms of
“arousal” on display that are there to be looked at, but always from afar, not too close,
without touching.
Box 2.8
“Si tu ne sais pas porter ton péché, il faut mieux le laisser aux experts.”
—Marcel Jouhandeau, sort of
Montréal is Sin City.
At least, that is what we are told. This catch phrase has become so familiar, it is now an integral part of
our local identity; our patrimoine. From booze smuggling to gang warfare to city hall corruption to the sex,
Sex, SEX, Montréal swaggers as salaciously as Sodom and Gomorrah once did, back in the day (without all
that messy fire and brimstone stuff).
This must be the grit to which many are referring; this must be the grit whose loss will be lamented due
to the Quartier des Spectacles project.
This must be the grit that has led Montréal to be known as one of the premier destinations for vice; for
all things smut.
So let’s turn this redevelopment scheme on its head. What if, instead of sanitizing another corner of
Montréal with a palette of grey and glass, we accentuated its scandalous side and created a veritable Sin
City? Spice things up: In the stew that is the Main, the current plans are salt. What Montréal needs is some
chilli.
— Émile Thomas, “Learning the Tricks of the Trade from the Real Sin City” (2009)
Authenticity
Locality. “We don’t want nobody nobody sent.” This was the title Milton Rakove gave to
his study of Chicago politics, but the sentiment extends to outsiders walking unawares into
the classic Chicago bar or Texas saloon. Locality highlights being from here, being rooted
in this place and this place only, untainted by alien customs. There is the local craft fair
and the micro brewpub, the antique shop and the old tavern est. 1908, the local parish
pastor and the high school football rival, all contrasted to the more universalistic ideals of
more globally oriented organizations like human rights groups or transnational
corporations. Sharon Zukin has stressed the attractive power of the local in farmers’
markets, citing anthropologist Michèle de la Pradelle’s discussion of a Provence
marketplace where “vendors dress in blue peasant smocks, speak a mixture of standard
French and local dialect, and personally vouch for the quality of the strawberries, green
beans, or melons at their stand. . . . The shoppers, for their part, search for the carrots that
bear traces of soil” (Zukin 2010, 120). If the local for some like Faulkner and
Dostoyevsky instills places with depth, uniqueness, and subtlety of character, for others
the local is always merely la province, overbearing, parochial, provoking the search for
more global and cosmopolitan scenes—a classic theme in novels from Stendhal to
Thomas Wolfe’s You Can’t Go Home Again.
Ethnicity. As a type of authenticity, ethnic customs suggest deep, unchosen, originary
practices, somehow resistant to and undiluted by a homogenizing, deracinated, abstract
global monoculture. Brown-Saracino again is helpful in documenting the powerful
imaginative grip of ethnic authenticity. In Chicago’s Andersonville neighborhood,
“Midsommar fest replicates a traditional Swedish rite, complete with May Poles.” In
Provincetown, Massachusetts, the annual “blessing of the fleet reinforces Provincetown’s
identity as a Portuguese fishing village.” There are “Olde Home Days” in Leyden and
Chinese New Year celebrations along Chicago’s Argyle Street (2009, 137). Sociologist
David Grazian’s Blue Chicago describes similarly powerful scenes created around
Chicago’s various blues clubs, noting how “according to many consumers, clubs located
in transitional entertainment zones with romantic and storied reputations seem less
commercialized and more special than those in the downtown area” (2003, 72). These
offer “the elderly black songster, the smoke-filled neighborhood blues bar, the sounds of
the city’s black ghetto.” The search for ethnic authenticity influences which musicians get
gigs and which shows audiences attend.
State. Historian Eugen Weber’s (1976) Peasants into Frenchmen described the often
painful struggle to redirect the allegiances of France’s rural peasantry from local customs
to the national state. Sociologist John Lie’s (2004) Modern Peoplehood extends similar
ideas more widely, charting the ways in which modern states transform populations
without deep national identifications into peoples with national identities, national
histories, national parks, national curricula, national flowers, national birds, and national
songs. These images of the state remain powerful. Think of the “Battle Hymn of the
Republic” on July 4 or “La Marseillaise” on July 14, walking through the battlefield at
Gettysburg or chanting the Pledge of Allegiance in public schools. International sports
events and Olympic competitions enhance such symbols, as do military parades on
national holidays in nations across the world. That some citizens reject such patriotic
efforts is true as it is of all scenes dimensions—they have both enthusiastic supporters and
hostile critics.
Box 2.9 Homebrew and the American Beer Renaissance
In 1979 there were 44 beer breweries operating inside the United States; today there are more than 1,400,
producing things like chocolate stouts, double bocks, and other craft brews. Now more styles are brewed in
America than anywhere else. The King of Beers, once served in splendid isolation at many bars, is now
surrounded by motley bottles with names as creative as their ingredients might sound: SkullSplitter, Old
Leghumper, Slam Dunkel, Troll Porter, Moose Drool, Power Tool, He’brew, and Ale Mary Full of Taste.
Local and regional beer has reemerged. Such breweries are often proudly and self-consciously local,
sporting local historical photos, maps, and other artifacts of a place’s personality as part of the decor.
Geographer Wes Flack has hypothesized that the growth of such establishments is a prime illustration of
a movement termed “‘neolocalism’ in which people are attempting to reconnect with the local, the personal,
and the unique” (Schnell and Reese 2003, 45). The owner of Stone Brewing Company in San Marcos,
California, says, “Our company logo and protector, the Stone Gargoyle, prevents modern day evils
(chemical preservatives, additives, and adjuncts) from tainting our beer” (60).
In “Microbreweries as Tools of Local Identity,” geographers Schnell and Reese conclude that among
microbrew beers, modern lifestyles are “almost always slighted in favor of historical, or at least blue-collar
lifeways such as blacksmiths, or miners, or steamboat captains. Nowhere did we find a Stockbroker Stout
or Systems Analyst Pilsner or C.P.A. I.P.A. Instead, Mine Shaft Stout . . . and Lumberjack Amber Ale . . .
are more typical. People who work with their hands, whose very livelihood is entwined with the geography
of where they live, are those used to represent the ‘true’ place” (2003, 59).
— Meghan Kallman
Corporateness. “You can’t beat the real thing.” This was the jingle made famous in
Coca-Cola’s early 1990s advertising campaign. Transnational, global, cutting across
states, regions, and ethnicities, the symbols of the modern megacorporation assert the right
to define what is genuine and what is not, claiming the allegiance of many. This is the
allure of Gucci bags versus knockoffs, Nike versus no-names, and Hard Rock Cafe fries
versus just plain old fries. Think of passing by a local cafe and heading into Starbucks,
securely confident in what the brand promises, solidly and reliably, from Seattle to the
Forbidden City. Jörg Marschall (2010) describes the enthusiastic groups gathered around
“Volkswagen classic car brand communities.” John Hannigan’s Fantasy City explores the
many corporate-themed restaurants, entertainment complexes, and museums increasingly
lighting up city centers from the United States to the Pacific Rim. He notes that visitors
often collect memorabilia branded with corporate logos as “‘passports’ . . . confirming that
the tourist has come and gone. . . . The Hard Rock Café chain has cleverly taken up this
ritual, with customers and servers buying and trading pins from the different Hard Rock
outlets around the world” (1998, 70). The brand says: something really happened and I
was there. Globally salient brands are also the most potentially vulnerable to rhetorical or
physical attack: anti-McDonaldization has become a symbol transcending one firm. The
website ihatestarbucks.com receives a steady stream of testimonials about the
inauthenticity of the Starbucks “experience.”
Rationality. The true self lies in the mind—this is the ideal of rational authenticity. The
spontaneous exercise of reason is deeper than the arbitrary and external circumstances of
location, ethnicity, or nationality. The intellect is pure, untainted by politics and
commerce. Novelist Saul Bellow found this principle in Chicago, which he called “a
cultureless city nevertheless pervaded by Mind” (1975, 69). Comedian Shelley Berman
found it in Hyde Park: “If you’ve never met a student from the University of Chicago, I’ll
describe him to you. If you give him a glass of water, he says, ‘This is a glass of water.
But is it a glass of water? And if it is a glass of water, why is it a glass of water?’ And
eventually he dies of thirst” (Dougherty and Cohl 2009, 93). Daniel Bell suggested that
books in contrast to movies cultivate the cognitive intellect. Readers approach books at a
self-determined pace, requiring more reflection on their images or symbols. Films sweep
audiences away; they are more likely to overwhelm with emotion. New York versus Los
Angeles for him typified the differences.
Urbanist Joel Kotkin’s idea of “Nerdistan” describes another variant: “largely newly
built, almost entirely upscale office parks, connected by a network of toll roads and
superhighways to planned, often gated communities inhabited almost entirely by college
educated professionals and technicians.” Nerdistans favor a “campus like environment”
catering to the tastes of the “science based society where power and privilege” belong to a
“new technocratic elite” (2001, 41). Not small, narrow streets quaintly winding their way
through organically formed neighborhoods, but rather grid plans and rationally ordered
addresses, stamped by the reasoning power of the human mind. Massachusetts Institute of
Technology buildings have no names, only numbers. The French Napoleonic tradition
produced kilometers of trees beside perfectly straight roads, and brought the world the
metric system and the numbered laws of the Code Napoléon, which in turn inspired
intellectuals, even Hegel, who joined the right and the rational in his Phenomenology. The
nineteenth-century romantics used rationality as foil, as did the postmodernists of the
1980s.
Box 2.10 Why Americans Love Chain Stores
“The Egyptians have pyramids, the Chinese have a Great Wall, the British have immaculate lawns, the
Germans have castles, the Dutch have canals, the Italians have grand churches. And Americans have
shopping centers.”
That’s a line from a 1996 paper by famed urban historian Kenneth T. Jackson. It’s pitch perfect not just
because comparing shopping centers to those other elegant accomplishments is ludicrous, but because the
uniformity of shopping centers stands in contrast to the individuality of the American spirit. . . . So what’s
the source of this gulf between our individual ideals and our common practice? A group of behavioral
scientists, led by Shigehiro Oishi at the University of Virginia, thinks it has to do with residential
mobility. . . . Oishi and colleagues believe American restlessness gives rise to the American strip mall.
Something about continual movement carries a concurrent urge for familiarity—like ordering the same
drink in any bar, perhaps. In short, movement breeds anxiety, and anxiety seeks stability.
At least that’s the theory put forth by Oishi and company in the Journal of Personality and Social
Psychology. The researchers defend their idea with a series of studies that examine the correlation between
mobility and strip mallery. In one test, they gathered 128 people into a lab, showed them a list of stores, and
asked them to choose which one they’d visit on a shopping trip. The list matched up national chains with
fictional stores that seemed to be local equivalents (e.g. Whole Foods v. Fresh Mart). They also collected
information about how often the participants had moved in the past. When they put this data together they
found that while everyone tended to like chain stores, there was a significant correlation between the
number of times a person moved and their preference for chains. “In short . . . personal history of
residential moves uniquely predicts preference for national chain stores over local stores. . . . Furthermore,
personal history of residential moves was the only significant predictor of preference for national chain
stores among 12 to 16 variables.”
— Eric Jaffe (2011)
Box 2.11
Faust’s battle with the elements appears as grandiose as King Lear’s, or, for that matter as King Midas’
whipping of the waves. But the Faustian enterprise will be less quixotic and more fruitful. . . .
. . . He outlines great reclamation projects to harness the sea for human purposes: man-made harbors and
canals that can move ships full of goods and men; dams for large-scale irrigation; green fields and
forests; . . . waterpower to attract and support emerging industries. . . . As Faust unfolds his plans, he
notices that the devil is dazed, exhausted. For once he has nothing to say.
As Faust surveys his work, the whole region around him has been renewed, and a whole society created
in his image. Only one small piece of ground along the coast remains as it was before. This is occupied by
Philemon and Baucis, a sweet old couple who have been there from time out of mind. They have a little
cottage on the dunes, a chapel with a little bell, a garden full of linden trees. . . .
. . . Faust becomes obsessed with this old couple and their little piece of land: “That aged couple should
have yielded / I want their lindens in my grip, / since these few trees that are denied me / undo my
worldwide ownership” . . . At this point, Faust commits his first self-consciously evil act. . . .
. . . He summons Mephisto and his “mighty men” and orders them to get the old people out of the way.
He does not want to see it, or to know the details of how it is done. All that interests him is the end result.
— Marshall Berman, All That Is Solid Melts into Air (1982, 62)
Legitimacy
Tradition. Tradition connects us to a past the weight of which informs our reasons for
acting in the here and now. The present moment is felt as organically connected to a
historical narrative whereby the wisdom of the ages continues to speak. Tradition is in the
scents and icons of the Catholic Mass when the millennia separating us from Christ melt
into nothingness, in the power of Doric columns to make our present practices and
mentality feel somehow in direct communication with their classical forebears. We feel
awe in standing on the shoulders of giants in sifting through archives, beholding
Renaissance paintings, or appreciating the classical musical canon. The final lines of Les
fleurs du mal embody the contrary, modernist sentiment, inviting the reader to leap “to the
depths of the Unknown to find something new!” (Aggeler 1954, “The Voyage,” VIII).
Tradition rules where the past is an enduring authority extending into the contemporary
world, in Catholic churches, classical music halls, and historical monuments rather than
avant-garde galleries, engineering firms, or the great industrial plant, where the rational
plan and the mighty machine make “history bunk.”
Charisma. Charisma creates legitimacy through the extraordinary qualities and
accomplishments of great figures. Charisma connects us to magnetically compelling
heroes, enjoining us to follow them, regardless of established rules and historic
conventions. John Potts’s A History of Charisma shows how the meaning has broadened
from Weber’s classic account while retaining many of its core elements: “The
contemporary meaning of charisma is broadly understood as a special innate quality that
sets certain individuals apart and draws others to them. . . . Charisma in contemporary
culture is thought to reside in a wide range of special individuals, including entertainers
and celebrities, whereas Weber was concerned primarily with religious and political
leaders. Contemporary charisma maintains, however, the irreducible character ascribed to
it by Weber: it remains a mysterious, elusive quality . . . challenging the ‘iron cage’ of
rationalization built in twentieth-century modernity” (2009, 3). Contemporary examples
include the sports hero’s signature inspiring a baseball with an auratic power, the
preacher’s words electrifying a room with the Spirit’s presence, and the rock star whose
singularity demonstrates that, in the words of Mick Jagger, “it’s the singer not the song.”
To envision an anticharismatic scene, think of Weberian and Kafkaesque imagery:
winding bureaucracy, forms in triplicate, and committees on committees.
Box 2.12
The print media allow for self-pacing and dialogue in comprehending an argument or in reflecting on an
image. Print not only emphasizes the cognitive and the symbolic but is also, most importantly, the
necessary mode for conceptual thought. The visual media—I mean here film and television—impose their
pace on the viewer and, in emphasizing images rather than words, invite not conceptualization but
dramatization.
— Daniel Bell, The Cultural Contradictions of Capitalism (1996, 108)
Box 2.13 Chinese Street Opera in Singapore
Sociologist Tong Soon Lee (quoted in Orum and Neal 2010, 188–89) describes how a Chinese Street Opera
company in Singapore’s Clarke Quay creates traditional legitimacy:
One of the most significant details in the entire spectacle at Clarke Quay is the emphasis on traditional
and historical features of old Singapore. The site itself, an important area in the history of the Chinese
community in Singapore, is a juxtaposition of historical reality, nostalgic sentiments, and
contemporary popular culture. . . . Some shops are modeled on historical interior architecture, and
restaurants are built on large traditional wooden boats know as ‘tongkang’ or bum boats, which are
replicas of traditional Chinese sailing ships used by Chinese immigrants to Singapore. The Chinese
opera stage itself, a simplified version of the traditional make-shift stage still used by professional
Chinese opera troupes today, symbolizes the persistence of a traditional Chinese cultural form,
reinterpreted in order to ensure its continuity in a changing contemporary context.
Utilitarianism. Instrumentalizing the current situation is the centerpiece of a utilitarian
basis of authority. Utilitarian legitimacy hews not to tradition or prophets but to Profit.
The value of a natural vista lies in the land rents extracted from it, of a human being in her
productivity, of an image in the value it adds to a product. Scenes of utilitarianism evoke
the importance of cold cost-benefit analysis and profitable production: in skyscraping
monuments to capitalism erected by investment banks, in the call to economize signaled
by management consulting agencies, in museums of industry and factory smokestacks. Yet
utility calculations can be rejected as well, in celebrating art for art’s sake, playful
uselessness, or purposeful inefficiency, as in slow food restaurants or taking the scenic
route.
Box 2.14
History is bunk.
— Henry Ford
Egalitarianism. That legitimacy depends on respecting human equality stands at the
core of egalitarianism. All people, close or far, high or low, deserve fair and equal
treatment. To make an exception out of oneself, to claim some special distinction to which
others are not entitled, becomes the essence of illegitimacy. The Christian injunction to
love thy neighbor is one of the deepest springs of egalitarian legitimacy; Immanuel Kant
redefined it in secular terms as the moral law. We see it in Salvation Army bell ringers, the
Universal Declaration of Human Rights, or Doctors without Borders. Alderman Paddy
Bauler declared the opposite: “Chicago ain’t ready for reform.”
Self-Expression. Self-expression bases legitimacy in the actualization of an individual
personality. The good person is one who brings her own unique take, her own personal
style, her own way of seeing, to each and every one of her actions. This is self-expression
as an ethical task, a demand to improvisationally respond to situations in unscripted and
surprising ways. Themes of self-expression run through Herder, Emerson, Thoreau, and
the American Pragmatists. Here is Emerson: “Insist on yourself; never imitate. Your own
gift you can present every moment with the cumulative force of a whole life’s cultivation;
but of the adopted talent of another you have only an extemporaneous half possession”
(2009, 145). The legitimacy of self-expression continues to be affirmed in improv comedy
theaters, rap cyphers, and karaoke clubs, in the stress on interior and product “design,” or
in the injunction to construct your own, unique iPod music playlist. Daniel Bell (1996)
suggested that this sort of outlook has come to dominate the contemporary art world from
conductors to poets, extending out from there to the general populace. Robert Bellah’s
(1996) famous case study in Habits of the Heart of a woman named Sheila showed its
religious potential—when asked if she believed in God, she replied, yes, I subscribe to
Sheilaism. Political scientist Ronald Inglehart (1977) has found evidence of an
international shift in values, away from “materialism” and toward personal selfdevelopment. Even so, hostility to self-expression can define a scene just as well, in
evincing the pleasures of fitting into scripts and filling roles—following in a marching
band, playing in lockstep with an orchestra, reciting a memorized prayer at Mass.
Box 2.15 Improv as a Way of Life
So why do they do it? The improvisers at the PIT are mostly in their twenties and thirties. They came to the
city after college to discover themselves, to become individuals. At some point in those first few months
they needed work and they got their first gig as a caterer or their first glimpse of real-life corporate culture.
Do you remember that moment? The surprise at seeing actual cubicles? The dronelike aspect of people just
a few years older than you? The humiliation of eating at your own desk? It’s a culture of boredom.
Everyone seems to be wearing a false face. Spontaneity is almost actively discouraged. You realize,
perhaps for the first time, how easy it is to be meaningless—even to be successful and meaningless. It is a
world most of us want to backpedal away from, but don’t know how. And then somehow the unicycle of
improv comes wobbling by. Is it any wonder we leap on it?
You take classes. In your very first improv class, you learn the orienting rule of the whole endeavor, the
rule of “yes-and.” The scene is built on this little engine. When your partner makes an offer, you’re taught
to agree to the basic premise of it (“yes”) and to add something of your own (“and”). But like many simple
maxims, “yes-and” proves to be an almost endlessly renewable resource. There are always more profound
ways to understand the value of “yes,” the value of “and.” Other frequently cited rules include “Listen and
react” (usually with a slow, hissed emphasis on “listen”), “Follow the fear,” “Commit, don’t comment” and
“Make your partner look good.” Beginning improvisers often wander around in a phase of revelatory
ecstasy in the weeks after they’re first exposed to these rules. Life suddenly looks like a stream of
improvised scenes (which of course it is), and one senses the potential of being able to invest every
interaction with a sense of discovery. Take risks, agree with people, commit completely to every
interaction, don’t deny the gifts others are offering you. Improv, one starts to feel sure, is a philosophy for
living, a way of finally being one’s complete self.
— Adam Bright, “Everything Alright” (2010)
A Combinatorial Logic of Scenes
These 15 dimensions are tools for decomposing any scene into a series of relatively
distinct elements. No doubt you could invent others. But rather than simply adding more,
how about trying your hand using these dimensions to color the scenes you pass through
on a typical day? Which have more self-expression than tradition; which are more formal
than transgressive; which evoke more of the authenticity of the local versus the corporate?
If these dimensions help to more precisely pinpoint and compare the character of the
scenes around you, they have served one purpose. Where and when you find yourself
running into some scene that seems to elude these dimensions, or some combination of
them, then adding a new dimension or redefining these 15 might make sense. This is just
the progress of science, whether natural, cultural, or social, and we encourage our
international collaborators—not to mention ourselves—to push on the margins of this
framework.
For building a theory of scenes, however, more pressing, and more theoretically
powerful than issues of completeness are issues of combination. Consider in this regard a
pregnant passage from Simmel’s Philosophy of Money, “It is not this or that trait that
makes a unique personality of man, but this and that trait. The enigmatic unity of the soul
cannot be grasped by the cognitive process directly, but only when it is broken down into a
multitude of strands, the resynthesis of which signifies the unique personality” (1990,
296). Now read the passage again, substituting words like “scene” and “place” for
“personality” or “man”: it is not this or that trait that makes a unique scene in a place, but
this and that trait. Or, the enigmatic unity of the scene cannot be grasped by the cognitive
process directly, but only when it is broken down into a multitude of strands, the
resynthesis of which signifies the unique scene. Certainly the 15 scenes dimensions
provide a multitude of strands; the question is how to resynthesize them.
Social Science in the Wagnerian Mode
The periodic table provides a powerful metaphor from the world of chemistry. But the
“total art works” of Wagner may be the best model from the world of culture, even if they
build on ground laid by others, like Stendhal in The Life of Rossini. Wagner’s leitmotifs
link recurrent themes to different characters, objects, and emotions, allowing the audience
to trace subtle connections across scenes. Leitmotifs could be sped up and combined with
each other to color a specific scene. Two melodies can be played against each other—
Wotan arguing with Fricka—while the background harmony is jealousy. Similarities
between two characters can be underscored by introducing them with similar but slightly
different themes. Conflict across families rings out in sonorous confrontations. Love,
anger, hatred, jealousy, nature, and death are all given fittingly constructed musical scores.
These motifs take on dynamic and larger meaning when combined. The Rhinemaidens’
joy coupled with Alberich’s pain evokes a deeper unity, musically and theatrically, as they
struggle for the Rhein’s gold. At the same time, just as characters have their own unity, so
may they take on a grander resonance when related to multiple leitmotifs. Loge’s
multifaceted character emerges more clearly when we see it from different angles across
six or seven themes. Having more themes permits more subtle combinations.
The music is then combined with the libretto, which Wagner stressed must be written
personally by the composer to authentically combine with the music and action of the
Gesamtkunstwerk, an aesthetically integrated whole, not just a superficial Italian “opera.”
The themes are distinctly powerful when they are constructed as abstractions of folk
music, as they then unconsciously engage the emotions of das Volk. Wagner, like Freud,
sought to dig deeply into the emotions, but each did so by writing long volumes trying to
deconstruct their subtle dynamics.
The great anthropologist Claude Lévi-Strauss (1969) drew explicitly from Wagner in
his Mythologiques, where he developed a basic grammar of mythological elements. A
similar sensibility is in some classics of sociology, even if the Wagnerian connection is
less explicit. Thus Max Weber’s (1930) ideal types articulate specific themes that help us
make relevant distinctions when analyzing phenomena. “The protestant ethic” does not
capture the full richness of capitalist culture, but it does provide a heuristic for comparing
one place or group to another along a number of dimensions. Talcott Parsons’s five pattern
variables function similarly. Extending the two classical types from Ferdinand Tönnies’s
Gemeinschaft and Gesellschaft—community and society, to which we return in chapter 3
—Parsons’s pattern variables decompose the two to permit multiple specific combinations
of analytical dimensions that can join differently in diverse contexts. A hospital includes
Gesellschaft-style dimensions like rationality and performance-based standards but also
Gemeinschaft-style dimensions like care and trust. The scenes dimensions extend this
tradition of theorizing.
Box 2.16
Using different genres of film music to underscore the neutral or ambiguous reaction shots of a character,
our experiments demonstrate for the first time that film musical schemas influence how much viewers like
or dislike a character and how confident viewers feel about how well they know a character’s thoughts. We
also found that in subsequently recalling the clips, viewers attributed to a character emotions that were
congruent with the context created by the musical genre.
These results support long-standing practices in the film industry. Since the silent era, compilers and
composers of film music have used musical schemas to guide audiences in their understanding of the
pictures. . . . Today this practice continues to be refined by companies that distribute production or library
music for a wide range of stereotypical genres to a host of media clients. While musical underscoring
reinforces or adds information to screen content, it provides guidance for audiences especially when
disambiguating neutral or ambiguous visual content, whose meaning is defined by the affective meaning of
the music. . . . Film composers and instructors of film scoring commonly speak of this practice as “music
doing all the work.”
However, our results also demonstrate that such powerful and distinct schemas as melodrama and thriller
music do not just follow conventional practices to fulfill cultural expectations by projecting sadness or
suspense onto the neutral or ambiguous reaction of a character, but also by influencing how viewers relate
to that character. The fact that film music has often been labeled as mood music . . . suggests that musical
moods are not only used to depict the atmosphere of a scene or portray the feelings of a character, but also
make viewers themselves experience that atmosphere and feel those feelings. Since music can both portray
and arouse emotions . . . underscoring not only helps viewers attribute to a character a certain state of mind
they recognize, but what they know about characters’ feelings may also influence how they feel about the
character.
— Berthold Hoeckner, Emma W. Wyatt, Jean Decety, and Howard Nusbaum, “Film Music Influences How
Viewers Relate to Movie Characters” (2011, 150)
Transforming a Scene into a Multidimensional Complex
If we think of the 15 dimensions as a set of leitmotifs, then we have a tool kit to do social
science in a Wagnerian mode. The key is to be sensitive to ways in which the “same”
motif can acquire different resonances when combined with others; and with this in mind,
to identify the basic character of any scene, especially those we care most about, from the
way that scene combines the whole 15 dimensional ranges of authenticity, theatricality,
and legitimacy.
An example helps to lend concrete meaning to this programmatic statement. Let us start
with Bohemia. There are a number of reasons for doing so. The mid-nineteenth-century
Parisian Bohemian quarters were some of the first spaces that concentrated and
legitimated aesthetic expression as a life project available to all. Self-expression often was
one part, maybe the key part, of this project, but the idea of “expression” in general goes
further. It is the difference between wearing a hat to protect yourself from the weather and
to reveal something about what you think is important or unimportant in life. What this
reveals can be, and in classic and contemporary Bohemias, often is, me; but it can just as
much say something about the value of nature, or God, or family, or anything else. The
attractive power of the original Bohemia derives in no small measure from licensing
people from all walks of life, not only the hereditary aristocracy, to engage in expressive
practices, to live life not only functionally and purposively but also aesthetically.
Beyond this general expressive orientation, Bohemia embodies a more specific ethos
that still speaks across generations. To the original Bohemians, given what they took to be
the dull, stifling character of their broader social environments—and with the censors of
Guizot looming overhead—the general expressive endeavor necessarily made them, at
least in their minds, into a small, oppressed collection of aesthetic elites. Bohemias thus
translated the general message of expression to a more specific aesthetic. What did it say?
That here is a place where normal social rules don’t apply, where you can express
yourself, in art and fashion or otherwise, in ways that the Establishment or
(anachronistically) “squares” would not understand and would likely find appalling, that
there is something authentic that resists planning, commodification, and
commercialization, whether that source lies in Nature herself or an ethnic or local heritage.
Here all of that—a Bohemian ethic—is not only permitted but positively encouraged,
much as the New England town might have encouraged the Puritan ethic.
Box 2.17
“There were no Baudelaires in Babylon,” wrote the Beat poet, Kenneth Rexroth—in ancient Babylonian
culture there was no place for bohemians. Equally in medieval and Renaissance Europe, the figure of the
dissident artist-rebel . . . would have been neither tolerated nor understood. . . .
The dominant Renaissance view of the artist had been of a well-adjusted individual. . . .
The Bohemian myth—the idea of the artist as a different sort of person from his fellow human beings—
is founded on the idea of the Artist as Genius developed by the Romantic movement in the wake of the
industrial and French revolutions. . . . Components of the myth are transgression, excess, sexual outrage,
eccentric behavior, outrageous appearance, nostalgia, and poverty—although wealth could contribute to the
legend provided the bohemian treated it with contempt, flinging money around instead of investing it with
bourgeois caution.
— Elizabeth Wilson, Bohemians (2000, 5–6)
This sort of imagery continues to exert a powerful allure. Richard Florida’s (2002) The
Rise of the Creative Class surely owes at least some of its success to the way in which it
plays with the classical idea of Bohemia. There is something tantalizing in the reversal
inherent in the idea that the key to economic growth lies not in the plodding
industriousness of the Puritan but in the dynamic experimentalism of the Bohemian.
Similarly, while the main purpose of Richard Lloyd’s (2006) Neo-Bohemia is to trace how
the classical notion of Bohemia morphed as traditionally countercultural lifestyles and
practices were progressively integrated into a much-expanded cultural economy, an
undercurrent is the persistent power of the idea of Bohemia itself, as young hipsters poke
around Chicago’s Wicker Park with copies of Les fleurs du mal and Les misérables in
their back pockets.
If we want to be more precise about what exactly this Bohemian spirit consists in, the
15 dimensions provide a useful way to do so. The logic is simple: go through each of the
15, and decide whether you think an ideal-typical Bohemian scene would positively value,
or negatively reject, each dimension. That is, ask yourself, would the perfect version of a
Bohemian scene proactively encourage one to present oneself in a transgressive way? If
the answer is yes, assign a positive score to the dimension; if the answer is no, assign a
negative score; if the answer is “Bohemia does not say anything very strong either way
about this dimension,” then assign it a neutral score.
Box 2.18
Disney Heaven: Sanitary, traditional themes, safe for children, low on crime,
pornography, prostitution, and homeless. Think of family restaurants, smiling waiters,
and Disneyesque staff who whisk away problems like dust. Buildings are clean and
freshly painted, albeit bland. Those that are grander reflect the dreamy Hollywood
vision of a European castle with smiling residents, rather than the Grimm Brothers’
tales or the scheming castle intrigues of Kozintsev’s 1964 film Hamlet. These themes
suffused the debates on Times Square when Disney acquired property there. Disney
asked the police to move out some of the disreputable. It coincided with Mayor
Giuliani’s endorsement of James Q. Wilson’s broken windows theory of crime scenes:
homeless, beggars, windshield squeegees, and drunks define an area as dangerous and
signal tolerance of this behavior by local citizens and the police.
The Samurai’s Licensed Quarters: To pacify politically dangerous warriors, centuries
back Japanese political leaders decreed “licensed quarters” where samurai could drink,
carouse, gamble, and enjoy Kabuki theater (which replaced female actresses with all
male actors after the women were carried off the stage by the enthusiastic samurai).
Ukiyo-E’s classic woodcuts depict related scenes, which inspired Impressionists, like
Toulouse- Lautrec and Van Gogh. Today in large Japanese cities highly demarcated
neighborhoods resemble Western “red light districts,” where indulgent styles of dress,
behavior, and entertainment contrast sharply with nearby neighborhoods.
Renoir’s Loge (Theater Box): Expressing an emerging interest in the spectacle and
theatricality of modern life, Renoir’s painting La Loge (Theater box) depicts an elegant
couple on display at the theater, capturing the drama and excitement of Parisian
fashionable society. The careful sensitivity of defining beauty in clothes, hairstyle, and
comportment is classic in television, Hollywood films, advertising, and women’s
magazines, as are reactions against them rooted in diverse traditions from Puritanism
to feminism to critical theory. We are surrounded with examples from media like
Women’s Wear Daily or Vogue or Elle, among others.
— The authors
Box 2.19
LA-LA Land Tinsel: The fluff, the icing on the cake, is the image here, above and
beyond the main event. The concept is close to Veblen’s conspicuous consumption or
Bourdieu’s “distinction,” illustrated by Louis XIV’s “superflu,” like Versailles
fireworks or Marie Antoinette’s comments about eating cake even when the poor are
beating down the gates. Restaurant reviews in the LA Times regularly comment on
which film stars dined in restaurant X recently, which clubs have the hottest lighting
engineers, what types of chocolate fountains have graced the best parties, and the like.
Currid (2007) explores similar themes in detail in the New York nightlife world, where
artists, fashion designers, musicians, and their hangers-on mix and mingle in exclusive
parties and clubs, which are transformed by their very presence into lucrative business
opportunities.
Rossini’s Tour: Every self-respecting midsized and large city in Italy in the early
nineteenth century sought to stage an opening night in their local theater, crowned by a
newly written Rossini opera, and, best, conducted by Rossini himself. He thus signed
up with dozens, but classically came into town the night before and delivered the
music so late that no one could check its originality before he was paid and left for the
next location. Stendhal’s Vie de Rossini is a brilliant source of observation on the
aesthetic components of such activities, starting from Rossini himself, but drawing on
Stendhal’s continual search for related charismatic cultural materials. The touring rock
star, surrounded by cheering fans, continues the scene, as does the summer jazz, folk,
or Bach fest, where internationally acclaimed musicians hold special clinics for
interested locals.
Brooks’s Bobos: Bohemian values and Bourgeois budgets combine in Brook’s (2000)
Bobos in Paradise amalgam, quintessentially illustrated by towns like Burlington,
Vermont, where latte spots offer expensive coffee, poetry, and antiestablishment
politics, which attract bearded professors with worn knapsacks riding old bikes.
Richard Florida draws heavily on Brooks (see Clark’s [2004, ch. 2] assessment and
critique). Florida’s argument is that the style has generalized nationally, and makes
some cities take off and be creative, attracting new and talented residents who bring
their Bohemian sensibilities to their work, as in the case of Steve Jobs, who told the
Pentagon in a security clearance application that LSD was a “positive life-changing
experience” and that hashish and marijuana made him “relaxed and creative” (Yglesias
2012). Woodstock plus Wall Street equals Silicon Valley is the Bobo formula.
— The authors
Table 2.3 represents our results for this exercise, where 1 is negative, 3 is neutral, and 5
is positive. The specific weights are extensions of themes from classical Bohemian
authors, like Murger, Rimbaud, Baudelaire, and Balzac, and recent investigators of
Bohemia like Lloyd or Elizabeth Wilson. Thus, to take a few examples, Rimbaud’s idea of
the value in the “systematic derangement of the senses” suggests a negative score on
rational authenticity while Baudelaire’s “aristocracy of dandies” suggests an
antiegalitarian tendency. That the allure of Bohemia aligns with a search for authenticity in
the ethnic is suggested by Baudelaire’s “The Swan,” which notably includes among its
“exiles” a “negress . . . trudging through muddy streets” (Aggeler 1954, II). And in
Lloyd’s update, for Neo-Bohemians, “sharing the streets with . . . nonwhite residents . . . is
part of their image of an authentic urban experience” (2006, 78). This inclusion of
multiple ethnic groups, even in conflict and possible violence, transforms grit into
glamour.
Table 2.3. Ideal-typical Bohemian scene
Dimension
Score
Dimension
Score
Dimension
Score
Traditionalistic
2
Neighborly
2
Local
3
Self-Expressive
5
Formal
3
Ethnic
4
Utilitarian
1
Glamorous
3
State
2
Charismatic
4
Exhibitionistic
3
Corporate
1
Egalitarian
2
Transgressive
5
Rational
2
Note: On each of the 15 individual dimensions, 1 is negative, 3 is neutral, and 5 is positive. Each US zip code receives a
Bohemian scene score by combining its scores on each of the 15 dimensions, weighting each of the 15 as in this table.
César and Marigay Graña’s (1990) On Bohemia: The Code of the Self-Exiled compiles
dozens of key documents in the history of Bohemia (see also Graña 1964). It provides an
indispensable source for understanding the subtle character of Bohemia, as does Elizabeth
Wilson’s (2000) Bohemians: The Glamorous Outcasts. And while there are of course
many subvariants, some of which we explore later (for instance, some versions are more
politically active, others more integrated into modern commerce), the 15 dimensions help
paint a numerical portrait of a typical Bohemian scene. Sketched in this way, a scene is
more Bohemian if it exhibits resistance to tradition, affirms individual self-expression,
eschews utilitarianism, values charisma, promotes a form of elitism, encourages people to
keep their distance, values fighting the mainstream, promotes ethnicity as a source of
authenticity, attacks the distant, abstract state, discourages corporate culture, and attacks
the authenticity of reason.
Yes, there is room for debate on this and any characterization of Bohemia. Indeed, part
of the power of the multidimensional approach to scenes is that it allows us to be precise
about where folks might disagree about the character of Bohemia or any other scene.
Perhaps you think that the tradition score ought to be a bit higher; you can redraw a
Bohemian scene thusly and then spell out exactly how and whether that difference makes
a difference.
Bohemia is of course just one scene. And without faulting its historic importance,
“Bohemian” still characterizes only a relatively small number of neighborhoods in a
relatively narrow corner of the world, even if the number is growing. But this is just the
point. Whole, complex scenes like Bohemia are much less general than the 15 dimensions.
You can choose any scene that characterizes your neighborhood, or city, or country, and
specify its character more precisely with the 15 dimensions. But that distinct combination
will describe a more specific scene, tied more directly to specific sociohistorical
circumstances, than will the abstract elements from which it is composed.
Thus any set of scenes (like Bohemia) that one analyzes will be somewhat arbitrary, as
it depends on the specific interests of the researcher. And specific weightings are open to
revision in the light of discussion and investigation. Still, the same general tools that we
applied to Bohemia can be used more broadly. We did this for several other scenes, like
Disney Heaven, descriptions of which run in the sidebar. While we do not elaborate most
of these in this book, introducing them here illustrates experimental possibilities for
playing with these scene concepts and extending them in new directions. International
collaborators have done just this to deconstruct crucial scenes in places like Seoul and
Paris.
Box 2.20
Wagner’s Volk: “Tragedy was therefore the entry of the artwork of the folk upon the public arena of
political life. . . . Tragedy flourished as long as it was inspired by the spirit of the folk.” Who are
das Volk? “The epitome of all those who feel a common and collective want.” Wagner wrote five
volumes of aesthetics developing this theory before he started writing The Ring. The core ideas
are close to those of Max Weber, Durkheim, Talcott Parsons, and others: basic values define a
coherent collectivity, a people rooted in shared history and symbols. Charisma is the degree to
which a performer can articulate deeply held common values in a new, emotionally charged
manner rooted not in the tastes of the few but the myths of the people. Folk musicians like Pete
Seeger, traveling around searching for music sung as an organic part of everyday life and informal
gatherings rather than as the complex productions of trained professionals to be performed for
paying customers, insisting that audiences participate and sing together as a group rather than
observe the pros in silence, carried on this tradition in the twentieth century.
— The authors
Box 2.21
Cool Cosmopolitanism: Globalization heightens the appeal of juxtaposing multiple conflicting
aesthetic criteria, like Tibetan female Buddhist monks chanting against electronica with ever more
mixing in the studio. Bertolt Brecht’s Theater of Alienation launched this aesthetic with a political
message: alienate the audience. So he added signs and more on stage. Peter Brooks applied this to
Shakespeare by adding a dozen pixies who threw paper airplanes at each other while the lovers
spoke their lines in A Midsummer Night’s Dream, thus distancing the audience from any one scene
but creating multiple, overlapping scenes competing for the eye’s attention. Susan Sontag’s (1966)
“Notes on Camp” is a more aesthetic version of Brecht’s political statement, a playful, alienated
denial of authenticity. Goffman’s (1974) Frame Analysis is written in the same spirit of this
transformational logic.
— The authors
Box 2.22
Black Is Beautiful: Some observe that low-status black areas are associated with storefront
churches and liquor stores that swamp other institutions. Others stress the cool, the music, the
subtleties of lifestyle as in Mary Pattillo’s (2008) Black on the Block. This is the image that the
Joyce Foundation sought to change by sponsoring classical music and more in poor Chicago
neighborhoods. The historical context of neighborhoods like Greater Bronzeville (in Harlem,
Newark, Oakland, Detroit, etc.), which lost most of their clubs, groceries, department stores, and
other “middle-class” amenities after the 1968 riots is explored in Lizabeth Cohen’s (2003) A
Consumer’s Republic. Do these locations attract more low-income black residents? Why? This
remains a hot policy question, elaborately debated from barbershops to BET (Harris-Lacewell
2004).
— The authors
A direct way to illustrate this transformational logic is with a matrix featuring the 15
dimensions along the side and more holistic scenes like Bohemia, Disney Heaven, or Cool
Cosmopolitanism across the top. Then we can join the rows and columns via simple plus
and minus signs (or numerical scores from 1 to 5). That is, we can use our dimensions to
conceptually define a Bohemia- or Disney Heaven–type of scene by articulating—in an
experimental and open-ended way—its archetypical qualities, its deep symbolic structures,
in terms of positive or negative weightings along the various dimensions of authenticity,
theatricality, and legitimacy. Table 2.4 is such a transformational matrix. It lacks
Wagnerian sounds and chemical smells, but they are on our to-do list.
Table 2.4. Joining complex scenes and scenes dimensions
Note: This matrix displays the 15 scenes dimensions as rows and the complex scenes like Disney Heaven as columns.
The cell entries are weights, with 5 signifying most positive. Darker shaded cells have higher values. Disney Heaven is
thus defined by the 15 weighted scores in the column below it: somewhat traditional but clearly not transgressive. The
matrix more generally illustrates the combinatorial logic of joining and weighting the 15 scenes dimensions to create
many other complex scenes.
Locating Scenes
Any theoretical construction implies something about how the objects it aims to represent
could be identified. How one conceives something shapes how one measures it. Details of
scene measurement will occupy us in the following chapter, but some general theoretical
principles deserve mention now.
Return again to everyday experience. Consider two ways you might identify scenes
around you. For the first, imagine a piece of paper with something like table 2.3’s ideal-
typical Bohemia printed on it. Put that paper on a clipboard, and start walking. For each
scene you encounter, estimate how closely it approximates the ideal type. Maybe it is
almost as transgressive as the ideal Bohemia, but a bit too traditional. Check off boxes
accordingly.
Write that information down on a piece of paper, being sure to record where you are.
After a while, you will have built up a nice database, in the form of a stack of paper. You
could then look back at your notes and compare each scene you visited in terms of how
Bohemian it is. Place 1 may come close to the Parisian ideal, while Place 327 may be far.
Even if nowhere matches the ideal type perfectly, you now have a measure of every
place’s relative Bohemianism. And if you think that Bohemianism correlates to, say,
changes in the makeup of the local residential population or new business formation, and
you knew how many people and businesses were located in the places you had visited,
you could test hypotheses about who moves to Bohemia and how businesses in Bohemian
scenes perform.
It would be hard, however, to go much further. What if you want to see patterns not in
one type of scene, or two or three dimensions, but in all 15 dimensions? Or to determine
how closely any actual combination comes to the most common or the most ideal-typical
ones? You would run out of paper pretty quickly. More important, it would be near
impossible to hold all this information together in your mind at once, even if you
somehow found the time and energy to visit tens of thousands of neighborhoods and cities.
It is precisely these sorts of limitations that lead one to try quantification, computers,
and statistics. By downloading information about hundreds of different types of amenities
for every postal code in the United States and Canada, we save ourselves the trouble of
visiting each one, and minimize the chances of error by relying on any one, dozen, or even
a hundred, indicators of the scene. This is of course not the only way to empirically
analyze scenes. Chad Anderson, for instance, used scenes concepts to analyze videos and
photos of neighborhoods in Seoul to understand the sources of a major conflict over the
city’s redevelopment strategies. Working in France, Stephen Sawyer used yellow pages
data to measure Parisian scenes, and one of his students made a film about one type, the
Parisian Underground, articulating its deeper dynamics. Numerous student papers have
investigated scenes ethnographically, especially around Chicago, and we sometimes draw
on these, such as Vincent Arrigo and John Thompson’s study of Bridgeport. We ourselves
have undertaken similar explorations of both Chicago and Toronto.
Still, by transforming digitized information about the location of hundreds of types of
amenities into numerical weights of the 15 dimensions, we can efficiently compare each
scene to one another across a more extensive geographic area. And by using some basic
statistical tools, we can see patterns and relationships among scenes that would be
otherwise hard to discern across so many cases and with so much information. Later
chapters employ such tools, like factor analysis, interaction terms, multiple regression
analysis, bliss points, hierarchical linear modeling, adjacency analysis, and more. While
these techniques may seem to create distance from everyday experience, they are in
essence nothing more than extensions of walking around and recording what you see, and
collating the results in various ways. So let us, then, start a tour around the scenescape,
and see what we find.
3
Quantitative Flânerie
Stephen Fry in America is a BBC television show in which Stephen Fry—a British actor,
author, playwright, and more—travels around America. The show’s conceit is that Fry’s
father almost took a job at Princeton, so that Fry himself was almost born an American. To
learn about the country that might have been his, Fry drives through all 50 states in a
London taxi cab, bringing a camera crew along for the ride to record the variegated scenes
of American life he discovers on the way.
Part of the show’s fun is that Fry does not refrain from expressing his judgments about
what he finds. The interface between people and horses in the Kentucky world of stables,
studs, racing, and grooming draws him in, while he suffers through a New Orleans voodoo
ceremony with a bemusedly ironic smile. A group of wise guys in a Queens social club
filled with sports memorabilia and ex-bookies fascinates him, while the architecture,
beach bodies, and nightclubs of Miami horrify him.
Stephen Fry in America extends the classic figure of the flâneur, famously captured in
the essays and poetry of Baudelaire and the novels of Balzac. For them, the flâneur
embodied a novel social type emerging in modern Paris. He would wander about the city
and observe the minute operations of daily life. For brief, punctuated periods, he would
plunge into some scene, tasting its flavors, listening to its sounds, smelling its scents, and,
ultimately, capturing its images and singing its songs in lyric poetry and impressionist
paintings. But he would take care to avoid losing himself in any specific scene, striving to
retain some distance, some space for reflection, some aloofness—all the better to remain
prepared to move on to the next scene, to compare it to the last, and to transmute it into
art.
In this way the flâneur distinguishes himself from both the activist and the mystic. In
contrast to the activist, the flâneur never fully, wholeheartedly commits to any scene in
which he participates; he keeps some part of himself in reserve. And unlike the mystic, the
flâneur does not withdraw from life into speculative contemplation; he is instead out and
about, on the streets, prowling the alleys. This makes the flâneur, as geographer David
Harvey puts it in Paris, Capital of Modernity, “more than an aesthete, a wandering
observer, he is also purposive, seeking to unravel the mysteries of social relations and of
the city” (2003, 56).
The Parisian flâneur is of course not the only type. The literature on flânerie and related
activities contrasts the nineteenth-century Parisian variant with similar social types
elsewhere. Balzac’s flâneur was creating an artistic interpretation of the city. He was
elevated and distant, admiring attractive buildings, cravats, and other walkers, but rarely
speaking to them—self-expressive, yet neither neighborly nor egalitarian.
By contrast the Spanish paseo or African American stroll included conversations with
others, striking a more egalitarian and neighborly pose (White and White 1998). And the
Parisian flâneur was a man; some women entered the Parisian streets behind veils in the
mid-nineteenth century, but their numbers leapt at the end of the century when department
stores emerged to replace the arcades and individual shops (Ferguson 1994; D’Souza and
McDonough 2008).
Similar changes emerged elsewhere. Chicago visitors in the early to mid-twentieth
century noted how fast people walked, as busy businessmen, lacking time to gaze or
ponder a cityscape, flew by. “One does not stroll in Chicago. Neither does one
contemplate. One goes and one does—at the greatest possible speed” (quoted in Harris,
n.d.). Yet by the twenty-first century, Chicago, like thousands of other cities, was covered
with Starbucks, bars, and restaurants. And some walkers slowed. Flânerie, of sorts,
entered, along with myriad other styles of street life.
Fry continues and updates this rich, multifaceted tradition of flânerie. But even with a
BBC budget, a London taxi, and a camera crew, he does not get to very many places in
very much detail in his six episodes and 50 states. This is understandable. The United
States is a very big place, with a host of different cultural traditions thrown together,
mixed and remixed many times over. No one person could take it all in on foot or by car.
And even if it could be done, it would be very hard not only to remember the sights but
also to properly compare one place to another. Yes, there are horse breeders in Kentucky
and clubs on Miami Beach, but how do we know if these places are truly distinctive?
Couldn’t similar scenes exist elsewhere?
The answer is to create a new type of flânerie for the digital age—quantitative flânerie.
One can observe the many scenes of North American life without leaving home. With
organizational directories from online sources and government statistics agencies, you can
get a surprisingly strong feel for the character of any given place. And since this
information is digitized, it can be entered into spreadsheets and used to compare the
scenes in all US zip codes (or Canadian postal areas) to one another.
We did this, for over 500 types of amenities in the United States and over 1,800 in
Canada. In this chapter, we introduce some of the results and the general contours of the
scenescape. We draw occasionally on scenes work in other countries. On the way, we will
also encounter some of the major methodological challenges one faces in trying to turn
information about the number of various types of amenities in different places into
information about the scene. Our solutions emerge in the process, as we introduce our
main measures of scenes and explain how we created them. But the more important goal is
to recalibrate our vision to be more sensitive to the world around us as not only a
landscape but also as a scenescape.
Amenities Data Are Windows onto the Scene
Suppose you wanted to catalog and compare as many scenes as you could but lacked the
resources to personally visit all of them. You could just give up there. But if you had some
friends who had already been to most every place you wanted to go and had taken good
notes on what they saw, you might be in luck.
To be sure, your friends, however careful they had been, were most likely not explicitly
looking for scenes. They had their own reasons for recording information about many,
many thousands of places. But their notes could still be useful, especially if they were
comprehensive. If your friends had used consistent classifications, so that when their
records say that Place 1 has 3 Xs and place 17 has 10 Xs, you could be confident that X
refers to more or less the same thing, that would be even better. And if the categories they
chose were detailed enough, you might be able to translate their records into different
terms that spoke more directly to the types of experiential dimensions characteristic of
scenes.
BIZZIP and YP, Two Main Scenes Data Sources
Think of the Census Bureau and the yellow pages as friends like this. Every year, the
Census Bureau collects comprehensive information about the total number of
establishments in every zip code. It calls its database Zip Code Business Patterns; hence
we refer to it often as BIZZIP. But the name is somewhat misleading, since in addition to
all sorts of for-profit businesses from fruit markets to graphic design firms, it also includes
information about nonprofit and government organizations, like art museums, religious
organizations, human rights organizations, civic and social organizations, and more.
Because of the misleading label and the fact that these data are hard to access, social
scientists have barely known of their existence, let alone analyzed them. We are among the
first.
The Census Bureau categorizes establishments according to a scheme called the North
American Industrial Classification System (or NAICS). The advantage of the system is
that it is relatively clearly defined, in general consistently applied across cases, and for the
most part available to public scrutiny—this is the Census Bureau after all. Moreover,
thanks to NAFTA, nearly all the same classifications are used in Canada and Mexico,
making international comparison easier. And we have examined data from other national
censuses, from Japan to Spain, that use closely similar formats and categories.
A disadvantage, for our purposes at least, is evident in the name, industrial
classification system. BIZZIP data are oriented toward production and taxes, toward
telling people the main types of work going on from place to place, not the main
experiences they might encounter. And BIZZIP categories are often not as fine grained as
we would like. For instance, they only tell us the number of restaurants and religious
organizations per zip code, not the number of fusion versus French versus diner
restaurants or the number of Catholic versus Jehovah’s Witness versus Baptist churches.
While, as we will see, these industry categories and broader classifications can still
yield highly useful indications of the character of the scene, some more detail would be
nice. This is where the yellow pages are helpful, which we call YP for short. They are
collected and organized with consumers rather than bureaucrats in mind, so they often
provide more specific information about qualitative experiential differences across
organizations. There are, for example, dozens of types of restaurants and churches listed in
the yellow pages, not to mention fishing lodges, nature parks, body piercing studios,
metaphysical bookstores, hemp shops, etiquette schools, Bible stores, and more. The
downside is that, compared to the census data, the collection protocols are less clear,
publically accessible, or consistently applied.
Despite their limitations, BIZZIP and YP are among the best data sources we have
found for measuring scenes;1 they have national and international coverage of local-level
units, and even given their vagaries, compared to alternatives, they use relatively clear,
consistent, and fine-grained classifications. While not perfect, they are at least as good as
many of the data sets that inform much social science research. We acquired from both
sources location information for around 520 types of establishments in the United States
and over 1,800 in Canada, where the smaller population makes it easier to compile more
types (the Canadian unit is called the Forward Sortation Area, or FSA, and is the first
three digits of the postal code).
Box 3.1 Beware, Your Imagination Leaves Digital Traces
The ancient divide between the social on the one hand and the psychological on the other was largely an
artifact of an asymmetry between the traceability of various types of carriers: what Proust’s narrator was
doing with his heroes, no one could say, thus it was said to be private and left to psychology; what Proust
earned from his book was calculable, and thus was made part of the social or the economic sphere. But
today the data bank of Amazon.com has simultaneous access to my most subtle preferences as well as to
my Visa card. As soon as I purchase on the web, I erase the difference between the social, the economic
and the psychological, just because of the range of traces I leave behind.
Dozens of tools and crawlers can now absorb this vast amount of data and represent it again through
maps of various shapes and colours so that a “rumour” or a “fad” becomes almost as precisely described as
a “piece of news,” “information,” or even a “scientific fact.” It’s not by accident that the founders of
Google have one reference in their original patent, and it is to a chapter of Robert K. Merton, the American
sociologist, about citation patterns in science.
Owen Gingerich, the great historian of astronomy, spent a life-time retrieving all the annotations of all
the copies of Copernicus’s first edition. He could thus give a precise meaning to the rather empty notion of
“Copernican revolution” and could show which parts of the book everyone had read and misinterpreted.
Nowadays, any scientist can do the same for each portion of each article he or she has published so long as
the local library has bought a good package of digital data banks. But what is more extraordinary is that any
journalist can do so as well for the latest Madonna video or the dirtiest rumour about Prince Harry’s love
affairs.
In other words, the former distinction between the circulation of facts and the dissemination of opinions
has been erased in such a way that they are both graduating to the same type of visibility—not a small
advantage if we wish to disentangle the mixture of facts and opinions that has become our usual diet of
information. Subjectivities used to be the inner sanctum where social sciences had to stop and dismount in
order to shift to other, less reliable vehicles. It is now possible to follow how the characters of a “reality
show” or the finalists of Star Academy have so modified the ways and means with which their viewers
speak and think about the world that the social has become, so to speak, continuous with the psychological.
— Bruno Latour (2007)
To be sure, both BIZZIP and YP tell us primarily about the buildings in a given zip
code. It would be nice to know more about who is there, what they are doing, how often,
with whom, and what they think of the experience. We can get at this a bit with the DDB
lifestyle survey, which Robert Putnam most famously used as the backbone of his analysis
in Bowling Alone. It has for decades asked representative samples of people questions
about how often they attend rock concerts, visit art museums, or go fishing, or whether
they agree with statements like “I am the car I drive” or “I am open to trying anything
once.” While we use the DDB occasionally throughout this book, it only goes down to the
county level, making it a useful supplement but not an ideal basis for scenes analysis, even
if it often provides a useful way to assess individuals’ consumption attitudes and
behaviors.
Still, though narrowly construed, BIZZIP and YP only tell us about buildings; this is
after all quite a bit, if we take an interpretative view of what a building means. For
instance, say we wanted to know where to find people adorning their bodies with images
versus teaching and learning. Finding out where there are more body art studios versus
schools would be a reasonable way to do so. Amenities data, that is, give us a glimpse into
the activities that typically occur in a given place, and this in turn is our window onto the
scene.
Two Problems: Trusting the Amenities Data; Making Them Sing
At this point, some questions naturally arise about the idea of using YP and BIZZIP data
to measure scenes. In the first instance, you might wonder how trustworthy these are as
indicators of the cultural characteristics of different places. Is the information they provide
reliable and valid; can we count on their counts? Can what are in the end organizational
directories really get at something as seemingly ethereal and ephemeral as the experiential
meaning of a place? Is it not the case that the number of establishments in a place is so
much a function of population, income, and density that looking for aesthetic meaning in
them is difficult at best and quixotic at worst?
In addition to these questions about reliability, there is also a question of translatability.
The theory of scenes in chapter 2 was not about amenities like community centers and art
galleries; it was about dimensions of meaning like neighborliness and self-expression.
How do we get from one to the other? How, that is, do we make the lines of cold digital
numbers sing in the key of scenes; how do we make them perform?
These are both hard problems without hard-and-fast solutions, and chapter 8, “The
Science of Scenes,” outlines some of the ways we’ve tried to address them. But the
general logic of the approach is intuitive enough. For the first set of questions, while there
are a number of ways, to use the technical term, to “validate” these types of data, there is
no foolproof method. The main question to ask is, do these data show meaningful and
intuitively credible patterns that reasonably conform to expectations? This need not mean
that every amenity count in YP or BIZZIP corresponds to what you would find if you went
out and counted the amenities yourself; YP and BIZZIP may undercount, say, the number
of playgrounds in New York and Chicago. But if the relative differences seem reasonable,
that may be enough, especially once we combine hundreds of them together, and check for
consistency across different data sources. The following section deals with these questions
in more detail by showing the extent to which the establishment data do indeed show
culturally meaningful variations from place to place. As always, there is some noise,
which later analyses and chapter 8 detail.
For the second set of questions, we had to work without a model. There is little
precedent for using these types of seemingly noncultural data as sources of information
about cultural meaning. One main response to the problem of getting the YP and BIZZIP
to perform is the performance score. The last section of this chapter illustrates what this
score is, how to make it, and how far it goes toward revealing the aesthetic qualities of the
world around us.
Amenities Data Reveal Plausible Cultural Patterns
Let us turn to the first set of questions, about whether these data sources tell us something
reasonably plausible about the cultural contours of North America. To do so, we return to
Mr. Fry, or at least the genre he represents. For Fry is in fact only the latest installment in a
long European tradition in which one travels around America to discover its distinctive
spirit. Alexis de Tocqueville is of course one of the most famous travelers, not least
because he transformed his observations into a powerful theory of the causes and effects
of democratic society. And one of Tocqueville’s intellectual heirs, Seymour Martin Lipset,
spent a career refining and extending Tocquevillian themes, highlighting especially the
extent to which many of the formative American experiences Tocqueville described
persist to the present, and often by contrasting the United States to its closest cousin,
Canada.
A look (in table 3.1) at the most numerous YP and BIZZIP items in our database shows
how much of what Tocqueville and Lipset saw remains encoded in the amenities that most
frequently dot the streets. Food, God, health, the law, the family, and the community
dominate the list. The typical American experience is saturated with spaces for shared
food consumption, personal care, adornment, self-presentation, worship, tending one’s
home and garden, and serving and connecting with one’s community. Indeed, BIZZIP lists
more civic and social organizations than beer and liquor stores (number 16, not shown in
table 3.1). America is also full of lawyers, expressing the formality and litigiousness
associated with the impersonal, egalitarian rule of law, which, as Lipset observed, often
translates into the rule of lawyers. And then there are the cars, a classic symbol of mobility
and individualism on the open road.
Table 3.1. Top 15 YP and BIZZIP amenities, nationally
Rank YP
Mean BIZZIP
Mean
1
Fast food restaurants
1.91
Full-service restaurants
4.56
2
Baptist churches
1.54
Law offices
3.97
3
Pizza restaurants
1.52
Religious organizations
3.92
4
Sports and recreation facilities
1.42
Landscaping services
1.71
5
New car dealers
1.41
Beauty salons
1.7
6
Hospitals
1.38
Grocery stores
1.62
7
Jewelers
1.31
Day care services
1.58
8
Bakeries
1.05
Hotels and motels
1.09
9
Antique dealers
0.75
Computer programming services
1.02
10
Methodist churches
0.74
Pharmacies and drugstores
0.95
11
Book shops
0.7
Gift, novelty, and souvenir stores
0.79
12
Health clubs
0.65
Civic and social organizations
0.75
13
Art galleries, dealers, and consultants
0.64
Convenience stores
0.72
14
Commercial artists
0.61
Furniture stores
0.71
15
Bar and grill restaurants
0.58
Jewelry stores
0.7
Note: This table shows the top 15 YP and BIZZIP amenities in our database. These are the mean number of each
amenity per zip code.
Even these simple national counts show the continuing power of Tocqueville’s
observations about how participatory, voluntaristic, legalistic, and localist the typical
American scene is. The strong strands of individualism, moralism, and civic activism that
(another Tocquevillian) Robert Bellah and his collaborators noted in Habits of the Heart
are clearly present in the national scenescape as well. The self-expressive dimension
appears here too in the numerous art galleries.
Cultural Differences Are Not Simple Functions of Population
Despite these similarities across the United States, visitors to America are perhaps more
often struck by its internal diversity. The yellow pages amenities help bring out this
variegated quality. First, look in table 3.2 at some of the highest-ranking zip codes for
some specific types of amenities. What is striking here is how little many of these
rankings have to do, at least on the surface, with demographic factors like population and
density. Thus, New York is indeed, as any foodie knows, the center of the restaurant
universe. All 10 zip codes with the most restaurants in the country are located in
Manhattan (numbers 11 and 12 are in San Francisco and Chicago). But even on food,
smaller places make the list, such as number 13 Myrtle Beach and number 16 Virginia
Beach.
Table 3.2. Top zip codes for restaurants, yoga, equestrian, golf, and bowling
Golf and
country clubs
Restaurants
Yoga
Equestrian
New York, NY 10013
(572)
Boulder, CO 80301
(15)
Versailles, KY 40383
(90)
York, PA 17404 (16)
Butler, PA 16001
(9)
New York, NY 10002
(282)
New York, NY
10001 (14)
Lexington, KY 40511
(75)
Palm Desert, CA
92260 (15)
Lafayette, IN
47904 (7)
New York, NY 10003
(228)
Frederick, MD
21701 (14)
Ocala, FL 34482 (52)
Dallas, TX 75234 (15)
Las Vegas, NV
89101 (7)
New York, NY 10019
(227)
New York, NY
10011 (12)
Lexington, KY 40507
(42)
Sun City West, AZ
85375 (13)
Toledo, OH 43615
(6)
New York, NY 10021
(219)
Los Angeles, CA
90035 (12)
Elmont, NY 11003 (34) Fayetteville, AR
72703 (10)
Hagerstown, MD
21740 (6)
New York, NY 10022
(195)
New York, NY
10023 (11)
Midway, KY 40347
(33)
Myrtle Beach, SC
29577 (10)
Lancaster, PA
17603 (6)
New York, NY 10014
(186)
Baltimore, MD
21218 (11)
Cave Creek, AZ 85331
(30)
Lincoln, NE 68512 (9)
Milwaukee, WI
53219 (6)
New York, NY 10036
(185)
Bethesda, MD
20814 (10)
West Palm Beach, FL
33414 (30)
Columbia Station, OH
44028 (8)
Atlanta, GA 30303
(6)
New York, NY 10012
(174)
Sarasota, FL 34231
(10)
Bend, OR 97701 (28)
Lancaster, OH 43130
(8)
New York, NY 10016
(155)
Ann Arbor, MI
48103 (10)
Petaluma, CA 94952
(24)
Sun City, AZ 85351
(8)
San Francisco, CA
94133 (154)
Chicago, IL 60614
(9)
Shelbyville, TN 37160
(24)
Naples, FL 34105 (8)
Chicago, IL 60610
(144)
San Francisco, CA
94102 (9)
North Fort Myers, FL
33917 (24)
Myrtle Beach, SC
29577 (143)
Santa Cruz, CA
95060 (9)
Fort Collins, CO 80524
(23)
Honolulu, HI 96815
(137)
Washington, DC
20001 (9)
Burbank, CA 91506
(23)
New York, NY 10011
(133)
Encinitas, CA
92024 (9)
Aubrey, TX 76227 (22)
Virginia Beach, VA
23451 (132)
West Chester, PA
19380 (9)
Cincinnati, OH
45208 (9)
Cedar Rapids, IA
52402 (9)
Bowling
52402 (9)
Note: This table shows the top US zip codes for restaurants, yoga, equestrian, golf, and bowling. Counts of each
amenity type for the zip code are listed in parentheses. The lists end at break points; for example, the zip code after
Cedar Rapids for yoga has eight yoga studios.
That variation in amenities follows cultural and not only demographic differences is
even more striking for more specialized amenities. Stephen Fry went to Kentucky and
found horses—no accident. The equestrian world is indeed focalized in Kentucky:
Versailles and Lexington host the most equestrian centers in the country, by a long shot,
and Paris and Midway also rank highly. Still, he could also have found numerous
equestrian amenities in Elmont, New York; Cave Creek, Arizona; Bend, Oregon; or
Burbank, California.
Other smaller places specialize in more niche lifestyle amenities. For example, yoga
studios: YP lists more for 80310 in Boulder, Colorado, than for the top zip codes in
Manhattan and Los Angeles. Yoga is popular in small college towns like Ann Arbor,
Michigan, and Santa Cruz, California, which are in the top 15 nationally. We examine
yoga and other “New Age” amenities in chapter 5.
Box 3.2 American Exceptionalism
America continues to be qualitatively different. . . . It is the most religious, optimistic, patriotic, rightsoriented, and individualistic. With respect to crime, it still has the highest rates; with respect to
incarceration, it has the most people locked up in jail. . . . It also has close to the lowest percentage of the
eligible electorate voting, but the highest rate of participation in voluntary organizations. . . . It is the leader
in upward mobility into professional and other high-status and elite occupations, but the least egalitarian
among developed nations with respect to income distribution, at the bottom as a provider of welfare
benefits, the lowest in savings, the least taxed, close to the top in terms of commitment to work rather than
leisure. . . .
Born out of revolution, the United States is a country organized around an ideology which includes a set
of dogmas about the nature of a good society. Americanism, as different people have pointed out, is an
“ism” or ideology in the same way that communism or fascism or liberalism are isms. As G. K. Chesterton
put it: “America is the only nation in the world that is founded on a creed. That creed is set forth with
dogmatic and even theological lucidity in the Declaration of Independence. . . .” . . . The nation’s ideology
can be described in five words: liberty, egalitarianism, individualism, populism, and laissezfaire. . . .
. . . Various seemingly contradictory aspects of American society are intimately related. The lack of
respect for authority, anti-elitism, and populism contribute to higher crime rates, school undiscipline, and
low electoral turnouts. The emphasis on achievement, on meritocracy, is also tied to higher levels of
deviant behavior and less support for the underprivileged. Intense religiosity is linked to less reliance on
contraception in premarital sexual relationships by young people. The same moralistic factors which make
for patriotism help to produce opposition to war. Concern for the legal rights of accused persons and civil
liberties in general is tied to opposition to gun control and difficulty in applying crime control measures.
The stress on individualism both weakens social control mechanisms, which rely on strong ties to groups,
and facilitates diverse forms of deviant behavior.
— Seymour Martin Lipset, American Exceptionalism (1997, 9, 26, 290)
This cultural diversity appears not only in the more specialized amenities but also in
some of those most abundant nationally. Many are not concentrated in major population
centers, despite their high national totals. Golf courses and country clubs are a good
example. They are in the top 40 most numerous amenities nationally. But they are most
numerous in places like Myrtle Beach, South Carolina; Sun City, Arizona; Naples,
Florida; and Palm Desert, California. Chapter 6 shows how strongly voting patterns track
concentrations of golf clubs and other “Blue Blood” amenities.
A similar pattern holds for more traditionally working-class amenities, like bowling
alleys, given iconic status in Robert Putnam’s Bowling Alone. These are more
concentrated in the American heartland: the top-scoring Manhattan and Chicago zip codes
are outpaced by places like Lancaster, Pennsylvania; Lafayette, Indiana; Toledo, Ohio; and
Milwaukee, Wisconsin.
Is the World Flat or Spiky? Probably Both
Another way to bring out what is shared across the typical American scenes is to look not
at total amenities but their distributions. Kurtosis is a statistical measure of how data are
concentrated or dispersed. High kurtosis indicates a few extreme observations, or peaks,
and then many lower ones, or valleys. Low kurtosis shows that most observations are of
about the same size, that the distribution is more flat.
This means that amenities with low kurtosis are found most anywhere you go. But high
kurtosis amenities are concentrated in a few places. See how much amenities differ in the
same 15 YP amenities from table 3.1—those with the highest average number per zip code
—when ranked by kurtosis in table 3.3.
Table 3.3. 15 most numerous YP amenities, ranked by their kurtosis
Rank
Amenity
Kurtosis
1
Jewelers
15401
2
Art galleries, dealers, and consultants
1694
3
Antique dealers
948
4
Hospitals
620
5
Commercial artists
601
6
Bar and grill restaurants
127
7
Baptist churches
56
8
Book shops
55
9
Health clubs
47
10
Methodist churches
37
11
New car dealers
35
12
Bakeries
33
13
Sports and recreation facilities
28
14
Pizza restaurants
17
15
Fast food restaurants
15
Note: This table ranks the 15 most numerous YP amenities (from table 3.1) according to their kurtosis. The kurtosis is a
simple statistic that shows how peaky the distribution curve is. A high score shows high peakiness and a narrow base. A
low score shows a wide base and low peak. Compared to a “normal” distribution, high scores show that if one considers
all US zip codes, only a few have the amenities with the high kurtosis scores.
Here are signs of both a common culture and strong local differences. The more local
and neighborly amenities like churches, pizza restaurants, bakeries, and sports and
recreation facilities are similar throughout the country. Corporate and utilitarian amenities
such as fast food restaurants and new car dealers are also flatly distributed. By contrast,
arts amenities, though abundant nationally, are concentrated in fewer places. Moreover, if
we look at amenities with the highest kurtosis nationally (not shown) we find them linked
with more specialized tastes. Some cater to illicit practices, like adult entertainment
products and casinos. Another group is more rarefied: fine dining restaurants, designer
clothing shops, wineries, theater companies and dinner theaters, and fashion designers.
Other peaky amenities include media organizations, like music publishers and cable
networks, and scientific research and development centers.
So is the world flat, as journalist Thomas Friedman suggests? On the one hand, these
simple tables bring home Richard Florida’s (2008) critique of Friedman: for the “creative
class,” the world is “spiky,” very unevenly distributed across space. Indeed, of the top 50
zip codes for independent artists, writers, and performers, not one, besides Nashville’s
37212, comes from outside the New York City or the Los Angeles area, and one must
scroll down to number 72 to find the next non-NY/LA zip code: Santa Fe, New Mexico.
Chapter 4 elaborates the economic consequences of these sorts of scenes. On the other
hand, some newer amenities are also broadly shared, like martial arts clubs (we elaborate
their distinctive role as social bridges in chapter 5).
Amenities Capture Subnational Cultural Differences
None of this is too surprising. We should not be shocked to learn that in the United States
pizza, burgers, cars, churches, and gardening are pretty much everywhere while fashion
designers, artists, and R&D labs are not.2 But that is precisely the point. That these data
sources confirm what we intuitively know about the scenes around us gives us more
confidence in them. This trust becomes especially important for later chapters, when we
find some surprising results with these same data.
So far we have discussed fairly large national aggregates. Yet as travelers like Fry have
always noted, there are clearly strong aesthetic, lifestyle, and cultural differences from
region to region and city to city. We would expect these to show up in our data, and they
do.
The South and Midwest Have More Churches; the West and Northeast Have More
Bakeries and Art Galleries
Consider the regional patterns in table 3.4. It shows the 25 most numerous types of
amenities from our yellow pages data in the South, West, Midwest, and Northeast.
Table 3.4. Top 25 YP amenities by region
Rank South
West
Midwest
Northeast
1
Baptist (2.53)
Fast food rest. (2.29)
Fast food rest. (1.72)
Pizza rest. (2.25)
2
Fast food rest. (2.08)
Jewelers (1.93)
Pizza rest. (1.55)
Sports and recreation
facilities (1.79)
3
Automobile dealers—
new cars (1.42)
Sports and recreation
facilities (1.67)
Hospitals (1.48)
Jewelers (1.76)
4
Hospitals (1.4)
Pizza rest. (1.58)
Baptist (1.32)
Automobile dealers—
new cars (1.62)
5
Sports and recreation
facilities (1.27)
Automobile dealers—
new cars (1.56)
Sports and recreation
facilities (1.26)
Bakeries (1.61)
6
Jewelers (1.21)
Bakeries (1.36)
Automobile dealers—
new cars (1.2)
Fast food rest. (1.54)
7
Pizza rest. (1.12)
Coffee houses (1.31)
Bar & grill rest. (1.15)
Hospitals (1.31)
8
Methodist (1.02)
Hospitals (1.29)
Lutheran (0.95)
Delicatessens (1.25)
9
Bakeries (0.85)
Artists—commercial
(1.16)
Catholic (0.84)
Antiques—dealers (1.1)
10
Cemeteries (0.73)
Art galleries, dealers &
consultants (1.13)
Jewelers (0.77)
Health clubs (0.85)
11
Automobile customizing
(0.63)
Book dealers—retail
(1.07)
Bakeries (0.76)
Artists—commercial
(0.76)
12
Book dealers—retail
(0.62)
Mexican rest. (1.01)
Methodist (0.76)
Book dealers—retail
(0.75)
13
Antiques—dealers (0.61)
Health clubs (0.93)
Antiques—dealers (0.63)
Art galleries, dealers &
consultants (0.75)
14
Sandwich shops (0.55)
Baptist (0.92)
Golf courses (0.56)
Bar & grill rest. (0.63)
15
Nondenominational
(0.54)
Antiques—dealers (0.88)
Book dealers—retail
(0.54)
Sandwich shops (0.63)
16
Health clubs (0.53)
Equestrian (0.75)
Health clubs (0.53)
Methodist (0.59)
17
Art galleries, dealers &
consultants (0.52)
Sandwich shops (0.68)
Libraries—public (0.5)
Ice cream shops (0.58)
18
Mexican rest. (0.49)
Cafes (0.64)
Cemeteries (0.49)
Chinese rest. (0.57)
19
Church of Christ (0.48)
Martial arts instruction
(0.61)
Golf courses—public
(0.48)
Catholic (0.56)
20
Church of God (0.48)
Chinese rest. (0.57)
Artists—commercial
(0.44)
Martial arts instruction
(0.54)
21
Equestrian (0.46)
Delicatessens (0.55)
Sandwich shops (0.44)
Dance cos. (0.53)
22
Pictures & prints—retail
(0.45)
Pictures & prints—retail
(0.55)
Ice cream shops (0.43)
Baptist (0.52)
23
Nightclubs (0.45)
Antiques and collectibles
(0.54)
Coffee houses (0.42)
Automobile customizing
(0.52)
24
Pentecostal (0.45)
Sportswear (0.54)
Art galleries, dealers &
consultants (0.41)
Coffee houses (0.49)
25
Chinese rest. (0.43)
Nondenominational
(0.53)
Automobile customizing
(0.38)
Antiques and collectibles
(0.47)
Note: This table shows the top 25 YP amenities within each US region (defined according to US census specifications).
Numbers in parentheses are the mean quantity of that amenity per zip code in the region.
Regional differences are strong. Consider religion. Churches are in the top 10 in the
South and Midwest but not the Northeast and West. The West and Northeast have more
bakeries, art galleries, bookshops, and health clubs than any type of church. Artistic
amenities also vary considerably by region. Zip codes in western states in fact have on
average over twice as many art galleries as found in the Midwest and South. Region is one
of the strongest classical bases of cultural variation, and it shows clearly in the yellow
pages.
Still, there is considerable overlap in amenities across the regions. Fast food restaurants
rank in the top 6 in all regions, and in the top 2 everywhere except for the denser
Northeast. McDonald’s is everywhere. Whether this portends the “McDonaldization of the
world” in the sense that the local, expressive, and charismatic are being overrun by the
rational and the utilitarian is a theme we explore in chapter 4.
Moreover, despite their differences, both the West and the South have large numbers of
equestrian centers and Mexican restaurants, while these amenities are not in the top 25 in
the Northeast and Midwest. The South, West, and Northeast all share a taste for jewelry,
which is in the top 6 for all three (the Midwest is more reserved and less glamorous:
jewelers are outranked by pizza restaurants, bar and grill restaurants, Catholic churches,
and Lutheran churches). Nor does their high numbers of churches mean that southerners
don’t have fun after dark: there are more nightclubs per zip code in the South than in all
other regions. While, as we’d expect, regional differences in the amenities supply are
strong, as we’d also expect, amenities crisscross the regions in numerous ways that go
beyond simple dichotomies. Or tetronomies, for that matter.
Despite Their Many Similarities, Big Cities Are Still Very Different Culturally
One of the foundational ideas in urban sociology, formulated classically by Georg Simmel
in his essays “The Metropolis and Mental Life” and “Group Expansion and the
Development of Individuality” (among other places), is that there is something sui generis
about urban experience (Simmel 1971). A big city is a big city is a big city. Density of
human contacts imposes a common stamp on the psychological makeup and day-to-day
interactions of urban dwellers, so that whether we are in Tokyo, Berlin, or New York,
similar social types and qualities appear—commercial, rational, distant, blasé, innovative,
hurried.
Scholarship since Simmel has rightly questioned this strong rural-urban divide. Still, it,
or its residues at least, emerge clearly in our amenities data. At the same time, there are
strong signs of deep cultural differences across New York, Chicago, and Los Angeles (not
to mention Toronto and Montreal) of the sort that have often impressed visitors and
observers—and this despite the fact that these cities are dense hubs of industry, commerce,
and the arts.
Table 3.5 compares the 40 most numerous yellow pages amenities (in our database)
across New York, Chicago, and Los Angeles, and figure 3.1 graphically displays some
others to make comparison easier. Note first that the three cities do, as one would expect,
share many common characteristics. Nearly three-quarters of the top 40 amenities in each
city are shared by all three.
Table 3.5. The top 40 YP amenities in Los Angeles, Chicago, and New York
Rank Los Angeles
Chicago
New York
1
Jewelers (7.58)
Jewelers (5.64)
Jewelers (13.28)
2
Bakeries (3.78)
Fast food rest. (5.43)
Delicatessens (6.02)
3
Fast food rest. (3.76)
Baptist (5.17)
Bakeries (5.66)
4
Artists—commercial (3.14)
Pizza rest. (5.11)
Art galleries, dealers & consultants
(4.91)
5
Automobile dealers—new cars
(2.69)
Bakeries (4.72)
Pizza rest. (4.82)
6
Pizza rest. (2.68)
Bar & grill rest. (4.68)
Sports & recreation facilities (3.96)
7
Sports & recreation facilities (2.51)
Hospitals (3.79)
Artists—commercial (3.76)
8
Coffee houses (2.19)
Sports & recreation facilities
(3.63)
Antiques—dealers (3.53)
9
Book dealers—retail (2.02)
Cemeteries (3.33)
Fast food rest. (2.78)
10
Children’s clothing (1.99)
Music stores (3.08)
Health clubs (2.37)
11
Baptist (1.96)
Automobile dealers—new cars
(2.95)
Chinese rest. (2.24)
12
Art galleries, dealers & consultants
(1.88)
Artists—commercial (2.76)
Hospitals (2.15)
13
Cafes (1.56)
Book dealers—retail (2.43)
Book dealers—retail (2.09)
14
Health clubs (1.53)
Catholic (2.28)
Automobile dealers—new cars
(1.95)
15
Mexican rest. (1.51)
Health clubs (2.12)
Sportswear (1.93)
16
Hospitals (1.5)
Coffee houses (2.11)
Bar & grill rest. (1.63)
17
Donut retail (1.47)
Art galleries, dealers &
consultants (2.1)
Baptist (1.61)
18
Antiques—dealers (1.42)
Sandwich shops (1.79)
Coffee houses (1.59)
19
Sportswear (1.39)
Lutheran (1.68)
Music stores (1.5)
20
Christian (1.35)
Nondenominational (1.66)
Pentecostal (1.5)
21
Talent agencies (1.3)
Mexican rest. (1.64)
Designer clothing & accessories
(1.43)
22
Martial arts instruction (1.18)
Antiques—dealers (1.58)
Cafes (1.35)
23
Sandwich shops (1.16)
Chinese rest. (1.43)
Nightclubs (1.23)
24
Fashion designers (1.07)
Family rest. (1.42)
Catholic (1.2)
25
Music stores (1.06)
Cafes (1.41)
Dance cos. (1.18)
26
Antiques & collectibles (1.04)
Delicatessens (1.37)
Martial arts instruction (1.15)
27
Chinese rest. (1.02)
Ice cream shops (1.35)
Fashion designers (1.13)
28
Tobacco stands (1.02)
Parks & playgrounds (1.34)
Ice cream shops (0.95)
29
Pictures & prints—retail (0.95)
American rest. (1.27)
Episcopal (0.94)
30
Nondenominational (0.93)
Children’s clothing (1.27)
Theaters—live (0.94)
31
Delicatessens (0.85)
Sportswear (1.2)
Italian rest. (0.9)
32
Ice cream shops (0.85)
Pentecostal (1.11)
Sandwich shops (0.89)
33
Cemeteries (0.78)
Martial Arts Instruction (1.1)
Pictures & prints—retail (0.88)
34
Exercise & physical fitness
programs (0.77)
Tobacco stands (1.09)
Seafood rest. (0.77)
35
Nightclubs (0.77)
Christian (1.05)
Antiques & collectibles (0.76)
36
Bail bonds (0.73)
Church of God (1.05)
Exercise & physical fitness
programs (0.75)
37
Dance cos. (0.71)
Pictures & prints—retail (1)
Donut retail (0.71)
38
Presbyterian (0.64)
Antiques & collectibles (0.99)
Japanese rest. (0.7)
39
Pentecostal (0.63)
Dance cos. (0.94)
Mexican rest. (0.68)
40
Newspapers (0.6)
Theaters—live (0.92)
Tobacco stands (0.68)
Note: These are the mean number of amenities per zip code (in parentheses) within Los Angeles County, Cook County,
and the five county boroughs of New York.
Figure 3.1
This figure compares selected (BIZZIP and YP) amenities per zip code within Los Angeles County, Cook County, and
the five county boroughs of New York. These are the mean number of amenities per zip code.
Yet differences also emerge. Consistent with their peakiness, jewelers are concentrated
in the country’s major cities: they are ranked first in all three cities. But in New York, YP
lists many more, reflecting New York’s strong position in the gem market but also likely
contributing to scenes of wealth and material abundance, not to mention the style of
“ambition”—“you should be richer!”—articulated by Paul Graham (see box 3.4). In laidback Los Angeles, cafes and coffeehouses (added together) nearly equal fast food
restaurants, while in Chicago fast food considerably outnumbers cafes and coffee shops.
Fast-paced New York City contains more delis than cafes and coffeehouses (nearly
double).
Box 3.3 Cities and Ambition
Great cities attract ambitious people. You can sense it when you walk around one. In a hundred subtle
ways, the city sends you a message: you could do more; you should try harder.
The surprising thing is how different these messages can be. New York tells you, above all: you should
make more money. There are other messages too, of course. You should be hipper. You should be better
looking. But the clearest message is that you should be richer.
What I like about Boston (or rather Cambridge) is that the message there is: you should be smarter. You
really should get around to reading all those books you’ve been meaning to.
When you ask what message a city sends, you sometimes get surprising answers. As much as they
respect brains in Silicon Valley, the message the Valley sends is: you should be more powerful.
That’s not quite the same message New York sends. Power matters in New York too of course, but New
York is pretty impressed by a billion dollars even if you merely inherited it. In Silicon Valley no one would
care except a few real estate agents. What matters in Silicon Valley is how much effect you have on the
world. The reason people there care about Larry and Sergey is not their wealth but the fact that they control
Google, which affects practically everyone. . . .
The big thing in LA seems to be fame. There’s an A List of people who are most in demand right now,
and what’s most admired is to be on it, or friends with those who are. Beneath that the message is much
like New York’s, though perhaps with more emphasis on physical attractiveness.
In DC the message seems to be that the most important thing is who you know. You want to be an
insider. . . .
At the moment, San Francisco’s message seems to be the same as Berkeley’s: you should live better. But
this will change if enough startups choose SF over the Valley.
— Paul Graham (2008)
Box 3.4 New York: Arguing the World
By the time Bell, Kristol, Howe, and Glazer arrived, the [CCNY] campus had become home to a feverish
student radicalism that burned with the concentrated energy of a hard, glowing ember. The defining issue
for these young radicals had become the nature of radicalism itself, a question posed by Soviet Russia, the
world’s first socialist state. Was Soviet leader Joseph Stalin the true prophet of Marxism or had he
corrupted the ideals and principles of the Soviet revolution? In the college’s cafeteria alcoves, radicals
gathered in constant, uninterrupted discussion from morning to night—the anti-Stalinist opponents of the
Soviet Union in alcove one, their Stalinist foes in alcove two. Of course, as City College alumnus Philip
Selznick recalled, “in those days having a discussion meant arguing about something and doing it at the top
of your lungs!” . . .
For early radical converts like Bell and Howe, the argument had begun even earlier, on the streets of
their immigrant neighborhoods. As young street corner speakers, they had harangued and argued with
impromptu crowds over the fate of the American economy and the blessings of socialism. But the nature of
the argument deepened, and changed at City College. Over the course of those years, Marxist thought
would provide a kind of mental chrysalis, allowing each young man to transform himself, almost
unconsciously, from would-be radical to nascent intellectual. They had thought that argument would help to
confirm the correct path toward political salvation, but in practice, their interest in politics proved a bridge
toward a life of intellectual inquiry. Partisan Review and its coterie of writers would inspire them to make
the crossing.
— Joseph Dorman, Arguing the World (2000, 2–3)
Nightclubs abound in New York: it has more nightclubs per zip code than Chicago and
LA. As do art galleries and dealers: over twice as many per zip code than in LA and
Chicago—here, as well as in the high number of designer clothing stores and fashion
designers, we see urban planner Elizabeth Currid’s “Warhol Economy” of fashion, art, and
music incarnate. The more intellectual character of New York’s scenes is present here too.
New York has the most book publishers, Los Angeles the least (though they are similar in
terms of bookstores). New York’s amenities, that is to say, indicate glimmering scenes of
intellectual and aesthetic sophistication, constant motion and profit seeking, and intense
urbanity. These are vital dimensions of experiences that New York offers to those who
live, work, and visit there. But they will not show up in measures of income or average
education levels.3
Box 3.5 LA: Sunshine Or Noir?
These, then, are the three major collectivized interventions by intellectuals in the culture formation of Los
Angeles: what I somewhat awkwardly abbreviate as the Boosters, the Noirs, and the Mercenaries. The
Exiles, as a fourth, more parenthetical, intervention, have linked the indigenous process of city-myth
production and its noir-ish antipode to European sensibilities about America and its West Coast. . . .
It is hard to avoid the conclusion that the paramount axis of cultural conflict in Los Angeles has always
been about the construction/interpretation of the city myth, which enters the material landscape as a design
for speculation and domination. . . . Even though Los Angeles’s emergence from the desert has been an
artifact of giant public works, city-building has otherwise been left to the anarchy of market forces, with
only rare interventions by the state, social movements or public leaders. The city’s most Promethean figure
—water engineer William Mulholland—was enigmatic and taciturn to an extreme (his collected works: the
Los Angeles Aqueduct and the injunction “Take it”).
— Mike Davis, City of Quartz (1990, 22–23)
California is virtually a nation unto itself, but it holds a strange hope, a sense of excitement—and some
terror—for Americans. As most of them see it, the good, godless, gregarious pursuit of pleasure is what
California is all about. The Citizens of lotusland seem forever to be lolling around swimming pools,
sautéing in the sun, packing across the Sierra, frolicking nude on the beaches, getting taller each year,
plucking money off the trees, romping around topless, tramping throughout the redwoods and—when they
stop to catch their breath—preening themselves on-camera before the rest of an envious world. “I have
seen the future,” says the newly returned visitor from California, “and it plays.”
— Time Magazine Staff, “California” (1969)
Los Angeles’s amenities suggest a different scene. Cars are important. Auto dealers
rank highly in LA; it has more classic car dealers than Chicago or New York. There are
numerous cafes and coffee shops for hanging out, as well as many working artists
(commercial artists are in the top 5). Indeed, in Los Angeles, YP lists more independent
artists, writers, and performers per zip code than religious organizations (the reverse holds
in New York and Chicago). With its many talent agencies (a top-25 amenity in LA, not in
the top 40 in New York or Chicago), aspiring stars are always on the scene. LA’s
numerous children’s clothing stores suggest a place where it is important to look good and
dress right, from the cradle on. And there are, of course, the movies: LA has the most film
production of the three. “You should be famous,” as Graham might put it, is built into the
city’s amenities.
Los Angeles is filled with cars, stars, bodies, and cafes, and these amenities help us to
measure and quantify main elements of the city’s distinctive feel. This Los Angeles image
was promoted by many media and developers into the 1930s, when it clashed with the
new migration of Oakies and European artists and intellectuals.4 They developed the film
noir, which dialogues with LA as Tinsel Town and Disney Heaven. Maps of Los Angeles’
scenes (see figure 3.6) distinguish the older downtown area, which remained WASPy into
the twenty-first century, from West LA (Hollywood, etc.), which housed the film industry,
more artists, and Bohemians. One potential indicator of LA’s dark side: there are more bail
bond providers per zip code in LA than in Chicago or New York.
The scene in Chicago is still different. Chicago’s traditional ethos is a blend of Catholic
neighborhood parishes and the friendly American small town, carried north in part by
African Americans. This ethos is present in Chicago’s amenities. Chicago is filled with
churches. Baptist churches are in the top 5 in Chicago while no church is in the top 10 in
New York or Los Angeles. And unlike any other major US city, Chicago is distinctly
Catholic: YP lists nearly twice as many Catholic churches per zip code for Chicago as for
New York and almost four times as many as for LA. Chicago also contains high numbers,
relative to New York and LA, of family restaurants, American restaurants, ice cream
shops, bar and grill restaurants, public libraries, cemeteries, and parks—classic Chicago
amenities which evoke the family, community, tradition, and neighborliness, like its
novelists from Nelson Algren to Andrew Greeley, and performers Walt Disney and Frank
Sinatra.
Box 3.6
Rap icon Ice-T’s 2012 documentary The Art of Rap explores the craft of rap artists. In a 2012 interview on
Bullseye, Ice-T describes the differences between the types of rap that emerged in New York and LA: “I
call [New York rap] verbal gymnastics. Let’s not just rhyme simple, to the 4-4. We’re going to intricate it,
make it in 16s. LA at that time was trying to define themselves. We had to let the world know what we
looked like. So while we were busy trying to define ourselves [in LA], which was pretty much a gang
culture, New York had taken it off into what in hip hop they call skills. They’re like OK, anyone can rhyme
4-4, but do you have skills, can you take it to the next level. So what I had to do was say, ‘I’m not maybe
going to have that verbal complexity, I have to rhyme heavy.’ . . . There’s no riddles in my rhymes, every
single word means something.”
— The authors
Shakespeare is renowned for his enormous vocabulary as well as his introduction of new words to the
English language—but can any modern-day writers compete with his literary skills? A New York data
scientist [Matt Daniels] not only proved that there are indeed contemporary lyricists that can give the
playwright a run for his money, he has also discovered that they come from an unexpected source—hip
hop. By comparing the works of Shakespeare with 85 different hip-hop artists, he found 37-year-old
Californian rapper Aesop Rock—who used 7,392 unique words in his first 35,000 lyrics—has a wider
vocabulary than the 16th century poet. By comparison, Shakespeare used 5,170 unique words, putting his
vocabulary alongside Beastie Boys and Outkast, while Moby Dick author Herman Melville scored 6,022,
only beaten by Kool Keith, GZA and Aesop Rock. . . .
Daniels also looked at where the rappers were from, to see if there was a vocabulary divide between
southern, midwest, west and east coast states. The south had the lowest average at 4,268, while the eastcoast, including 50 Cent and Fat Joe, scored highest with 4,804.
— Victoria Woollaston, “Does Wu-Tang Clan Really Have a Bigger Vocabulary than Shakespeare?” (2014)
Box 3.7
Chicago succeeds by offering the benefits of density while still remaining affordable and pleasant. The
city’s economy depends on information-intensive industries, like finance and business services, that seem
to particularly value density. Financial entrepreneurs, like the billionaire hedge-fund manager Kenneth
Griffin, choose Chicago because it has the size and the well-educated workforce to provide the
professionals and services that their organizations need, while still maintaining a strong quality of life and a
family-friendly wholesome Midwestern feel, as compared with Manhattan.
— Edward Glaeser, The Triumph of the City (2011, Kindle location 4188)
Yet these scenes marking the power of the traditional and the neighborly are joined by a
New Chicago, shown in cafes and coffeehouses, commercial artists, health clubs, art
galleries and dealers (all in the top 25), as well as more custom computer programmers per
zip code than in either New York or Los Angeles. Chicago’s amenities, that is, suggest
both scenes of its small-town accent on tradition, neighborliness, and local authenticity
and newer scenes where cafe and gallery culture mix with commerce and technology. The
amenities data flag the distinctive feel of Chicago—a wholesome and neighborly smalltown scene plus a strong knowledge economy—but in quantitative, cross-city ways that
match what sophisticated observers have already noted on more impressionistic bases.
From Amenities to Scenes
Our friends the US Census Bureau and the yellow pages seem to be generally reliable
informants. Their data have considerable face validity, to use the social science term for
intuitive plausibility. They match informed expectations about the character of cities. This
in turn gives us more solid grounds for assessing the surprisingly strong, and often
counterintuitive, findings that flow from them below.
Still, YP and BIZZIP only tell us about pubs and playgrounds, galleries and garden
centers. What we want to know about is neighborliness and self-expression, transgression
and tradition. How do we get from one to the other?
Single Amenities Can Give a Misleading Impression of the Overall Scene
As a first step, note that analyzing only one or a handful of amenities may be misleading.
But this is in fact what most past amenities studies have done—they look separately, for
instance, at museums, restaurants, live performance venues, bowling alleys, movie
theaters, and coffee shops.5 These studies, even after subjecting their results to intense
statistical scrutiny, have nevertheless found startlingly strong consequences flowing from
these amenities—like population growth where there are more restaurants and live venues,
and crime reduction where there are more cafes. This is a testament to the general idea that
amenities matter for urban development.
To get a read on the overall feel of a place, single or small batches of amenities can lead
us astray. One or a few amenities are not necessarily representative of an overall scene.
This is a critical point of the whole scenes approach. Consider the general principle more
concretely.
Table 3.6 shows the top 15 or so amenities in 4 of the 10 zip codes with the most body
art and piercing studios in the United States. Downtown Boston houses 02118, in the
ethnically diverse, gay-friendly, and culturally active South End neighborhood. Downtown
Baton Rouge has 70806, which includes the historic Capitol Heights neighborhood. In
92109 there is San Diego’s Pacific Beach neighborhood, replete with surfers, nightlife,
and singles. The zip code 30338 is in Dunwoody, Georgia, in the suburban fringe of
Atlanta.
Table 3.6. Amenity profiles in four zip codes with numerous body piercing studios
South End,
Boston 02118
Capitol Heights, Baton Pacific Beach, San
Rouge 70806
Diego 92109
Dunwoody,
Atlanta 30338
Artists—commercial
(17)
Baptist (25)
Sports and recreation
facilities (23)
Fast food rest. (13)
Body piercing (15)
Hospitals (16)
Tattooing (19)
Body piercing (11)
Seafood rest. (14)
Antiques—dealers (15)
Health clubs (18)
Jewelers (7)
Pizza rest. (12)
Body piercing (13)
Pizza rest. (17)
Sandwich shops (7)
Baptist (12)
Jewelers (12)
Automobile dealers—new
cars (17)
Sports and recreation
facilities (6)
Bakeries (9)
Sports and recreation facilities
(8)
Tobacco stands (14)
Health clubs (6)
Art galleries, dealers &
consultants (9)
Book dealers—retail (8)
Boat & yacht charters,
rental & leasing (14)
Methodist (5)
Cafes (8)
Automobile dealers—new cars
(7)
Mexican rest. (13)
Coffee houses (5)
Antiques—dealers (6)
Health clubs (7)
Fast food rest. (12)
Dance cos. (5)
Artists—fine arts (6)
Pictures & prints—retail (6)
Coffee houses (12)
Exercise & physical
fitness programs (5)
Sports and recreation
facilities (5)
Fast food rest. (6)
Bar & grill rest. (12)
Methodist (5)
Tattooing (6)
Body piercing (11)
Parks & playgrounds (5) Full Gospel (6)
Cafes (11)
Note: These are approximately the top 15 amenity types for 4 of the 10 US zip codes with the most body art and
piercing studios. The lists were cut off at the point where the total amenities including ties came closest to 15. Counts of
the number of amenities in each zip code are in parentheses.
Our yellow pages database lists for each many body art and piercing studios: 11 in
Dunwoody and Pacific Beach, and 13 and 15 in Capitol Heights and South End,
respectively. But the rest of the amenities in each zip code differ (we also discuss
amenities not in the table).
For instance, South End, Boston, joins body piercing with cafes, fine artists, art
galleries, and a few designer clothing stores. By contrast, in Capitol Heights, Baton
Rouge, along with the body piercing, are over two dozen Baptist churches and several Full
Gospel churches, interdenominational churches, cemeteries, bookstores, and antique
dealers. Pacific Beach has more sports than arts, mixing both with nightclubs, yoga, and
diverse restaurants. By contrast the mix in Dunwoody, Atlanta, is more classically
suburban: fast food restaurants, gyms, and sandwich shops—yet no nightclubs and the
fewest arts amenities of the four. Places strong in the same single amenities clearly diverge
in their overall amenity mixes.
Box 3.8 What’s the Deal With Dunwoody?
Question: I’m looking for areas to live in the North/Northeast part of atlanta. Working rather far up I-85.
I’ve been looking into Dunwoody and surrounding areas. Single young female. . . . Any suggestions?
I’ve heard good things about Dunwoody, just not so sure what’s there to offer. Any fun bars/shops etc?
If not, any suggestions for locations on the perimeter or near??? Thank you in advance!
Answer: I grew up in D’woody and recently moved back after getting married. It is cooler than it used to
be but still not exactly a utopia for someone who is single. The only real bars in actual D’woody are
Dunwoody Tavern and Timmy’s Village Pub, and they are pretty basic pub/tavern type places.
Perimeter Center has places that are basically just restaurants with bars, like Taco Mac, but still not
exactly crazy nightlife. When I was single I lived in Midtown and Virginia-Highlands and loved it—
honestly, these are the better areas for someone who wants to have a good time and meet cool new
people. Agree with posters above that D’wood is straight up family livin’.
— City-Data (2007)
Making Amenities Sing: The Performance Scores
With just a handful of cases it is possible to compare the overall set of amenities in this
way. But even for just four it is not only time-consuming but also difficult to look up and
down the list for each zip code while remembering and processing what is in each. To do
this across the board is humanly impossible.
This is why aggregating amenities is essential to create distinct measures of scenes with
coherent cultural meaning. In other words, we need some way to see in the digital rows
and columns of numbers aesthetic performances. The performance score is a useful
response to this problem.
Chapter 8 describes how to create performance scores in more detail, but the basic
principle is relatively straightforward. It is similar to the transformational matrix in
chapter 2. We assign to each amenity a positive or negative weighting (from 1 to 5) on
each of the 15 dimensions. That is, adult entertainment venues would be scored high on
transgression but low on neighborliness; etiquette schools high on formality but low on
exhibitionism; punk music clubs high on self-expression but low on corporateness.
A team of coders assigned these weights to all amenities in our database. They used a
series of standardized questions, from a manual called “The Coder’s Handbook.” We all
met regularly to discuss our assumptions, revise our questions, and check for consistency.
We brought in new coders to see if they would produce similar scores. Table 3.7 shows
some illustrative samples of amenities that we decided to use as positive indicators of each
dimension—but keep in mind that these are only a small subset from the whole, which
includes hundreds more positive and negative indicators.
Table 3.7. Scenes dimensions and their amenity indicators
Theatricality: Sample amenity indicators
Glamorous
Fashion shows & designers; designer clothes & accessories; beauty salons; nail salons; motion
picture & video exhibition; motion picture & sound recording studios; agents, managers for artists &
other public figures; film festivals; nightclubs; jewelry stores; casinos
Formal
Formal wear & costume rental; opera companies; fine dining; private clubs; dance companies;
nightclubs; golf courses & country clubs; theater companies & dinner theater; religious organizations;
offices of lawyers; professional organizations
Transgressive
Body piercing studios; tattoo parlors; adult entertainment: nightclubs; adult entertainment: comedy
and dance clubs; leather clothing stores; skateboard parks; casinos; beer, wine & liquor stores;
gambling industries; hemp shops
Neighborly
Bed & breakfast inns; civic & social organizations; religious organizations; golf courses & country
clubs; sports teams & clubs; playgrounds; elementary & secondary schools; fruit & vegetable
markets; coffee houses; pubs; baked goods stores
Exhibitionistic Adult entertainment: night clubs; fashion shows & designers; body piercing; tattoo studios; health
clubs; fashion shows & designers; beauty salons; nail salons; discotheques
Authenticity: Sample amenity indicators
Local
Bed & breakfast inns; historical sites; fishing lakes & ponds; marinas; book dealers: used & rare;
antique dealers; scenic & sightseeing services; nature parks & other similar institutions; spectator
sports; sports teams & clubs; microbreweries; fruit & vegetable markets; meat markets
Ethnic
Gospel singing groups; martial arts instruction; Afghan restaurants, African restaurants, Armenian
restaurants, Basque restaurants, soul food restaurants, Ethiopian restaurants, Irish restaurants,
Caribbean restaurants, Mexican restaurants, Italian restaurants (approximately 40 ethnic cuisines);
yoga studios; African art galleries
Corporate
Marketing research; management consulting services; warehouse clubs & superstores; designer
clothes & accessories; fast food restaurants; business & secretarial schools; department stores;
convention & trade shows; public relations agencies; spectator sports; amusement & theme parks;
advertising & related services
State
Political organizations; embassies & delegations; historical sites; American restaurants
Rational
R&D in physical, engineering & life sciences; scientific R&D services; colleges, universities &
professional schools; planeteria; aquariums; human rights organizations; management, scientific &
technical consulting; exam preparation & tutoring; libraries & archives; computer training; offices of
lawyers
Legitimacy: Sample amenity indicators
Traditional
Genealogy societies; historical sites; opera companies; antique dealers; fine arts schools; libraries &
archives; family restaurants; family clothing stores; religious organizations; dance companies;
museums; etiquette schools
Utilitarian
Fast food restaurants; technical & trade schools; warehouse clubs & superstores; business &
secretarial schools; management consulting services; convenience stores; business associations;
junior colleges; computer systems design; database & directory publishers; exam preparation &
tutoring
Egalitarian
Human rights organizations; Salvation Army; public libraries: elementary & secondary schools
(public); environment & wildlife organizations; junior colleges; services for elderly & disabled
persons; social advocacy organizations; individual & family services; religious organizations
SelfExpressive
Dance companies; fashion shows/designers; yoga studios; art dealers; comedy clubs; body piercing;
tattoo parlors; recorded music stores; vintage & used clothing; custom printed t-shirts; music
festivals: fine arts schools; graphic design services; independent artists, writers & performers;
musical groups & artists; performing arts companies; sound recording industries; hobby, toy & game
stores; interior design services; karaoke clubs
Charismatic
Designer clothes & accessories; fashion shows/designers; motion picture & video exhibition; art
dealers; dance companies; historical sites; political organizations; capitols; motion picture & sound
recording industries; musical groups & artists; performing arts companies; promoters of
entertainment events; spectator sports; fine arts schools; sports bars; sound recording studios
Note: This table shows illustrative samples of some of the amenities scored positive on each of the 15 dimensions.
We multiply the coders’ weights by the number of each amenity type (e.g., 3 adult
entertainment venues) in each zip code. More adult entertainment means a higher output
of transgression. These results (the number of adult entertainment amenities times its 15
dimensional weightings, etc.) are then added together. This gives 15 measures of the total
amount of self-expression, glamour, local authenticity, and so on, projected by the total set
of amenities in each zip code. We call these the 15 “intensity scores.”
From here it is one more step to the performance score. Simply divide the intensity
score by the total number of amenities of all types in the zip code. This performance score
is the zip code–wide average for each of the 15 dimensions. That is, it tells us the degree
to which the average amenity in any given zip code supports, attacks, or is neutral with
respect to the 15 dimensions of theatricality, authenticity, and legitimacy. Performance
scores are not rankings, but tools for discerning what types of experiences a given locale
specializes in, symbolic meanings defined in a score that can be analyzed further, as we do
below. This approach has also been used in Spain and other countries, with specific
analytical steps explained and results clearly mapped online for individual Spanish cities,
by our collaborator Clemente Navarro, in English and Spanish: http://scenes.enlinea.eu/en/.
Telegraph and Transgressies
An example provides a more concrete sense to the performance scores. First conjure up a
mental picture of Berkeley’s Telegraph Avenue in the early 1970s. There would be pipe
shops, revolutionary bookstores, street vendors selling Marxist bumper stickers, hemp
necklace dealers—an experience supersaturated with transgression, oozing through the
cracks in the dirty streets.
Now imagine Chicago’s Wrigleyville, circa 2006. The picture would include a few
tattoo parlors, some adult stores, a hip 24-hour diner. But it would also contain the Cubs
baseball team, Miller Lite beer promotions, snarky improv comedy troupes, and a few
Starbucks. Yes, a little bit of edge, but tempered by a corporate atmosphere, the tourist hub
that is the Wrigley Field baseball stadium, and the young urban professionals in the local
sports bars.
Box 3.9 The Poetics of Space
[Poetic treatments of space] seek to determine the human value of the sorts of space that may be grasped,
that may be defended against adverse forces, the space we love. For diverse reasons, and with the
differences entailed by poetic shadings, this is eulogized space. Attached to its protective value, which can
be a positive one, are also imagined values, which soon become dominant. Space that has been seized upon
by the imagination cannot remain indifferent space subject to the measures and estimates of the surveyor. It
has been lived in, not in its positivity, but with all the partiality of the imagination. Particularly, it nearly
always exercises an attraction. For it concentrates being within the limits that protect.
— Gaston Bachelard, The Poetics of Space (1964, xxxv)
Each of these scenes is distinctive. Berkeley is filled with displays of transgression,
different ways of showing off one’s resistance to authority, stability, order, fixed standards
—the average experience is intense. In Wrigleyville, transgression coexists with a whole
range of other experiences; the youthful rebellion is more muted.
The performance score is sensitive to the overall experience promoted by all of a
scene’s amenities. Boiling these examples down to their essence shows this. Let us
imagine an absolutely pure transgressive scene—Telegraph to the max. And let us say that
this scene contains five amenities, and that all are body piercing/tattoo parlor/water pipe
stores. These would therefore all receive a score of 5 on transgression—each one is
putting out five units of transgressiveness (five “transgressies,” we could say). The sum
total of transgressiveness in the scene would then be calculated by multiplying each of the
five amenities by its transgression score of 5, which equals 25 transgressies. If we divide
the total (25) by the total number of amenities in the scene (5), we find that the average
experience of transgression in this scene is . . . 5!
Now, consider what the performance score on transgression would be for a
Wrigleyville. Let us say that in this scene there are two body piercing salons, four bars,
two Chinese restaurants, and one Starbucks. In this case, the piercing salons would receive
5s for transgression, the bars (full of rowdy drunks) might receive 4s, the Chinese
restaurants 3s (neither promoting nor denying antiestablishment self-displays), and the
Starbucks a 2.
By multiplying the number of each type of amenity by its transgression weighting, we
see that the body piercing salons would be putting out 10 transgressies, the bars 16, the
Chinese restaurants 6, and the Starbucks 2. If we sum those, we find that the whole scene
provides 34 units of transgression. Divide that total (34) by the number of amenities in the
scene (9), and we can see that the average experience of transgression per amenity in this
scene is . . . 3.8. This is still more than a neutral experience, which we defined as 3, but
not as intense as Telegraph’s 5. A graphical illustration of these types of calculations is in
chapter 8.
Taking the Scenic Route
Clearly there are numerous inferential steps involved in making performance scores. But
all knowledge involves inferences, even classical concepts that have historically defined
the social sciences. For instance, who has ever seen custom? Or local authenticity? Yet
even if we cannot see local authenticity (or glamour, for that matter), the performance
scores allow us to compare the degree to which the average amenity in every zip code
features them.
Further details about how we came to an agreement about what weights to assign to
each amenity, checked for consistency among coders, and evaluated the reliability of the
measures are in chapter 8. The central goals were consistency and transparency. Others
may alter, delete, or add dimensions, or choose to code the same data differently, and
examine the results. Any such alteration will still produce a holistic understanding of the
scene in a particular location. The meanings that constitute a scene are, by their nature,
largely aesthetic. Accordingly, any serious study of these spaces as scenes will be an
interpretive rendition.
Social scientists from across the spectrum, positivist and postmodernist alike, could
follow this approach and get similar results. We do not argue that the results are the only
valid ones, but that they are as reliable—or consistent in the measurement theory sense of
consistency—as most similar social science. And small individual disagreements about
weightings—of which you would probably have a few—become trivial with hundreds of
thousands of data points. The huge number of cases adds statistical robustness and
consistency even when the models are slightly altered.
The performance scores provide our main measures of scenes. They focus our analytical
attention not on this or that specific amenity but on the more general cultural meanings
they express. Still, we are not methodological dogmatists, and often use other measures.
For instance, combining distinctive amenities in new indexes is often helpful for engaging
with specific debates and concepts and stressing key drivers of some scenes. Thus chapter
5 examines the types of residents who live near “New Age” amenities (e.g., yoga studios
and meditation centers) and “new conservative churches” (e.g., Pentecostal and Church of
Christ); chapter 6 analyzes the political contribution patterns of places filled with “Blue
Blood” amenities like golf and tennis clubs. Similarly, we often combine performance
scores with other measures to get a more specific picture of the scene: chapter 6 thus
measures “Bobo” scenes as the combination of high rent and transgressive amenities. And
we experimented with many other ways of constructing scene variables with amenities
data, such as brightness scores, and a cultural diversity index. Many are reviewed in
chapter 8.
Beyond Body Piercing
But rather than bogging down in methodological arcana, we can just take a bite from the
pudding, for in this lies its proof. To do so, let us pass through again some familiar
territory, this time taking the scenic route.
Consider first those same four zip codes we looked at before, the ones similar in having
numerous body art and piercing studios but different in many other ways. By transposing
them into the key of scenes (as in figure 3.2), we can readily summarize the differences
while at the same time comparing these zip codes to every US zip code.
Figure 3.2
This figure shows z-scores of five performance scores for four zip codes among those YP lists with the most body art
and piercing studios in the United States. These scores show the strength of these scenes dimensions in these places
relative to the national average (scored 0). The differences in each zip code’s overall scene profile illustrate how no
single amenity and no single dimension defines the total scene.
Figure 3.2 shows “z-scores” for five performance scores, meaning that the scores are
adjusted by the national average (scored 0). First note, as we would expect, the common
dimension of transgression, on which all four zip codes are well above the national
average. But then look at the other dimensions. Dunwoody (Atlanta) stands out as the
most utilitarian, Capitol Heights (Baton Rouge) as the most neighborly, Pacific Beach
(San Diego) as the most informal. All have higher glamour scores than the national
average zip code, but South End (Boston) has the highest, Dunwoody the lowest. The
performance scores readily bring into view both the commonalities and distinctions in the
scenes generated by local area amenities—and they give us a basis for efficiently
comparing these specific zip codes with many, many others.
To be sure, personal inspections of these places could bring out more subtlety, as could
analysis of more dimensions. So could inspecting the hundreds of individual amenities
generating our scenes performance scores. But for assessment of how these four compare
and contrast with one another and with the average US zip code, the performance scores
provide useful summary measures. And they can in turn be linked with other data to assess
the contributions of scenes to economic, residential, and political changes, as we show in
later chapters.
Scenes from New York, Chicago, and Los Angeles
In a similar way, the performance scores efficiently summarize the overall aesthetic and
lifestyle similarities and differences in the typical scenes of New York, Chicago, and Los
Angeles that we saw above in comparing their amenity profiles.
Figure 3.3 shows the mean YP performance scores of all zip codes within Los Angeles
County, Cook County, and the five county boroughs of New York (these are again “z-
scores”). We see here simply in the overall shape of their profiles what it took
painstakingly counting each amenity to see before: namely, that despite dramatically
different geographies, immigrant groups, political cultures, and economic specialties, the
three overall scenes profiles are quite similar, relative to the country as a whole. Compared
to the average US zip code, that is, scenes in these three cities affirm self-expression and
utility over tradition. They encourage transgressive, glamorous, and exhibitionistic styles
of theatricality more than formality. They root authenticity in reason, the state, and the
corporate brand more than in locality. And they showcase scenes rich in ethnic symbols.6
Figure 3.3
This figure shows z-scores of the mean YP performance scores of all zip codes in Los Angeles County, Cook County,
and the five county boroughs of New York. These scores show the strength of these scenes dimensions in these cities
relative to the national average (scored 0). As these are averages across large metropolitan areas, particular places within
them often differ from the area-wide mean. For instance, though the average zip code in New York and Chicago is less
neighborly than the national average, many zip codes in the South and West Sides of Chicago and in Staten Island are
more neighborly.
What the early twentieth-century urbanist Louis Wirth (2004) (following Simmel)
called “urbanism as a way of life” clearly continues in the late modern city, as more
abstract, formal, distanced social relations are linked with heightened individualism and
weaker primordial ties. All the same, important differences emerge. The average scene in
Chicago is more traditional, neighborly, and egalitarian and less transgressive, selfexpressive, glamorous, exhibitionistic, state-oriented, and rationalist than in New York or
Los Angeles. Los Angeles’s scenes are the most self-expressive; New York’s are the most
glamorous, ethnic, and transgressive, though the differences between Los Angeles and
New York are often small.
Performance Scores Reveal Spatio-cultural Relationships
The plausibility of these patterns in the performance scores across the three cities builds
more confidence in this way of comparing the character of one scene to another. We can
go still further by recalling a key point from chapters 1 and 2: different relations and
combinations of dimensions reveal different overall scenes. Now we can see that process
on the ground, empirically—both in spatial relationships, where the meaning of a scene
shifts from its proximity to others nearby, and in cultural relationships, where different
combinations of the same dimensions in different places yield different overall scenes.
Box 3.10 Chicago’s Local Pubs
Chicago consistently ranks higher than NYC and LA on neighborliness scores, in large part due to the
abundance of parks, pubs, and public libraries. A recent article, written by New Yorker and Economist
blogger Ryan Avent (2010), lamented the lack of a local pub scene in America and claimed that Europe’s
neighborhood bars are a mark of its superiority. This article invoked the wrath of loyal Chicagoans on
blogger Andrew Sullivan’s (2010) website, who responded with e-mails such as “Obviously these writers
have never been to Chicago.” Another reader writes: “At least on the north side, it’s tough to walk more
than a couple of blocks without running into a decent neighborhood bar of the type Avent describes. Damn
good beer these days too. I moved here from DC about a year ago, and the ubiquity of great corner pubs
with good burgers and friendly bartenders . . . made for one of the nicest welcomes I’ve ever received in a
new city.” “Here in Rogers Park, the most northerly neighborhood along the lake, we have quite a
collection to explore. From my front door it is exactly one block to our local bar. . . . Push the boundary to
three blocks and you have six neighborhood bars. . . . Once again, the rest of the country knows nothing
about life in Chicago, but we have, throughout almost the entire city, what the rest of you are missing.”
These e-mails both exemplify the metrics used to determine neighborliness and highlight the difference
between Chicago and other US cities.
— Meghan Kallman
Proximity Alters Performance
Suppose we have two iron filings, #1 and #2, more or less physically identical. However,
they differ in one important respect, their location. Filing #1 is at point (a,b), and Filing #2
is at point (x,y). The points (a,b) and (x,y) are, let us say, very far from one another. At the
same time, a magnet, M, is a few inches from (a,b) but hundreds of miles from (x,y). The
electrons in Filing #1 become aligned with the flow of the magnetic field around M while
the electrons in Filing #2 remain randomly polarized. Owing to nothing more than their
different locations in space, the two filings acquire different properties and exhibit
different movements.
In much the same way, highly similar scenes in two different locations can become
“different” depending on the other scenes nearby. Maps help show these sorts of spatial
relationships.7 Look first at figure 3.4, which shows tradition across all Canadian FSAs
and in the three biggest Canadian cities: Toronto, Montreal, and Vancouver. It maps
deciles of traditional performance scores across all Canadian FSAs and in these cities.
Darker areas have more traditional scenes, lighter have less.
Figure 3.4
These maps show the level of traditionalism by deciles for all Canadian FSAs and within each of Canada’s three largest
census metropolitan areas (CMAs). Darker areas have more traditional scenes; lighter areas less. Dotted lines indicate
census subdivision (CSD) boundaries, that is, the municipalities of Toronto, Vancouver, and Montreal.
Cities Resist Tradition, in Multiple Ways
Nationally, we see a division between more traditional scenes outside the major cities and
less traditional ones within the cities—a dark sea with light islands. However, there are
local pockets of antitradition in rural areas, mostly connected with large-scale industry.
And there are strongly traditional scenes within the major cities. Toronto has the lowest
average traditionalism, Vancouver has the highest, and Montreal has the most intense
pockets (the highest maximum, not shown). General cultural patterns are mediated by
local variation. Canada’s major cities, though generally antitraditionalist, continue to offer
scenes rooted in the authority of the past; the countryside, though generally more
traditional, offers some scenes that place rationality and freshness over entrenched custom.
Now look more closely within Toronto and Montreal, in figure 3.5, at spatial patterns in
three scenes dimensions: rationalism, self-expression, and transgression. Table 3.8
summarizes some of the amenities from our Canadian database weighted positively and
negatively on these dimensions.
Figure 3.5
These maps show levels of three scenes dimensions in Toronto and Montreal census divisions: rationalism, selfexpression, and transgression. Relative to the FSAs within each city, darker areas are higher on each dimension, lighter
lower. Scores are grouped according to Jenks natural breaks.
Table 3.8. Illustrative sample of amenities weighted high and low on traditionalism,
self-expression, transgression, and rationalism
Traditionalist
Self-expressive
Transgressive
Rationalist
Higher Bibles, synagogues,
weights clergy, archives,
religious goods,
religious
organizations,
etiquette, ethics &
protocol lessons,
antique dealers,
cemeteries,
monuments, heritage
buildings,
consultants,
bookbinders—
specialty &
restoration,
campgrounds, crests,
mausoleums,
historical places,
museums, fishing &
hunting, automobiles
—antique & classic
cars, opera
companies, church
furnishings &
supplies, churches &
other places of
worship, mosques,
synagogues
Artists—fine arts,
nightclubs, fashion
stylists & consultants,
haute couture, graphic
designers, clowns,
tattooing, piercing &
body art, schools—
dramatic art & speech,
art galleries, dealers &
consultants, estheticians,
dancing instruction,
interior designers, sound
recording studios,
musical groups &
artists, theater (except
musical) companies,
hobby, toy and game
stores, dance
companies, live theaters
& other performing arts
presenters with
facilities, yoga
instruction, independent
artists, writers &
performers
Sex shops, adult
entertainment, tattooing,
piercing & body art,
motorcycles, escort
services, hemp products,
casinos, nudist parks,
snowboards, smokers’
articles, gambling
industries, esotericism—
products and services, surf
shops, nightclubs, haute
couture, art schools, escort
services
Microscopes, telescopes,
encyclopedias, business
consultants, accountants,
lawyers, banks,
bookkeeping services,
insurance agents & brokers,
tax return specialists,
laboratories, management
consultants, economic
consultants, retirement and
planning consultants, labor
relations consultants,
engineers, patent agents,
expertise & technical
analysis, productivity
consultants, marketing
consultants, industrial
consultants, robotics, R&D,
forensic services, statistical
services, astronomy,
geophysical surveying &
mapping services, technical
& trade schools
Lower Business centers,
weights laboratories,
marketing
consultants, robotics,
administrative
management &
general management
consulting services,
engineers, industrial
consultants, machine
shops, multimedia,
hydroponics
equipment &
supplies, internet
cafes, wireless
communications,
computer supplies &
accessories, market
research & analysis,
R&D, sex shops,
escort services,
esotericism—
products & services,
inventors
Uniform rental services,
military goods,
etiquette, ethics &
protocol lessons, Bibles,
business centers,
business consultants,
engineers, technical &
trade schools,
accountants, lawyers,
management
consultants, corporate
image development
services, insurance
agents & brokers, stock
& bond brokers, tax
consultants, mosques,
synagogues, religious
organizations, law
courts
Military goods, etiquette,
ethics & protocol lessons,
formal wear, uniform
rental services, clergy,
Bibles, business & trade
associations, chamber of
commerce, accounting
services, lawyers, banks,
tuxedos, insurance, homes
—elderly people,
investment banking,
portfolio management,
mosques, uniforms,
religious organizations,
synagogues, religious
goods, antique dealers,
senior citizens services &
centers, child care services,
image consultants, elected
government
representatives, courts of
law, professional
organizations, children &
infants clothing stores
Esotericism—products &
services, clergy, Bibles,
mosques, funeral homes,
religious organizations,
synagogues, cemeteries,
churches & other places of
worship, astrologers,
psychic consultants,
massages, homeopathy,
aromatherapy, naturopaths,
chiropractors, amusement
places, pilates, health
resorts, nature parks, nature
centers, rock climbing,
skating rinks, boxing
instruction, psychotherapy,
hypnotherapy, sports teams
& clubs, acupuncturists,
herbal products, bars &
pubs, psychoanalysis,
musical groups & artists,
dance companies, beauty
salons, campgrounds,
funeral homes
Here we can see alternative versions of antitraditional scenes. Fitting with classic
depictions of major cities as disruptive of traditional customs and beliefs, Toronto and
Montreal are light across most FSAs (in figure 3.4), and their average tradition scores are
well below the national mean. Yet there are many ways to reject tradition, and these are
deeply embedded in these cities’ scenes. Thus, as figure 3.5 shows, rationalism makes the
scene in their downtown cores and in some suburban areas, but other parts of each city
have strongly antirationalist scenes. These are often defined by self-expression, which is
concentrated in Montreal’s famous Plateau area and in Toronto in the neighborhoods
surrounding the downtown core (such as the Annex, the Entertainment District, and Queen
West in the west, and Leslieville and the Beaches in the east). If we add transgressive
theatricality to the mix, we can also see the aesthetic distinction between the more
countercultural West End scenes in Toronto and the more local and neighborly East.
That contemporary cities are often generally antitraditional but defined by alternative
and sometimes opposing ways of rejecting tradition, whether through personal
spontaneity, defying conventional standards of dress and appearance, or the resolute
adherence to functional rationality, is of course a classic theme in the literature on
modernism and its discontents. But now we can pinpoint where these themes are located
and pose testable questions about their social consequences.
Just as important, and extending the iron-filing metaphor, the maps show revealing
differences in the spatial patterns of scenes. For instance, in Toronto, the city’s most
intense scenes of self-expression and transgression are often directly adjacent to its most
rationalist and utilitarian. By contrast, in Montreal there is typically a gradual movement
from one to the other while at the same time some of the most intensively rationalist
scenes are also highly transgressive.8 Here we see how Toronto’s strong split between its
(historically Victorian, WASP) establishment and its newer alternatives is built into its
everyday experience, with the most extreme versions of each facing the other cheek by
jowl.9
Maps of Chicago and Los Angeles are just as revealing. As figure 3.6 shows, in
Chicago, the South and West Sides of the city have the most neighborly scenes. The city’s
highest levels of self-expression are strongly clustered in the Near North Side. In Los
Angeles, high self-expression scores are spread out among a much greater geographic area
stretching mostly along its West Side, cutting the city near in half, from Hollywood
through Santa Monica and Malibu. By contrast, these areas are low on neighborliness,
which is higher in the Mexican American neighborhoods to the south but still quite broad
(remember that these scores are created purely from local firms/organizations, not
demographic characteristics of residents).
Figure 3.6
These maps depict Chicago and Los Angeles neighborliness and self-expression performance scores by standard
deviation from the mean. There is a difference in the number of divisions across the maps, from four to seven breaks.
Each city is compared only against itself in value because the standard deviations from the mean of each performance
score have been calculated individually for each city. Therefore, the individual maps only show the spread of
performance scores within a city. In the map of Chicago neighborliness, the range of scores is approximately between
−0.50 and 1.5 standard deviations from the mean, whereas Los Angeles presents a wider range, with values falling −1.5
to 2.5 standard deviations from the mean. This shows that Chicago has more similar and clustered values of
neighborliness across zip codes than does Los Angeles. The figure also shows that Chicago scenes are on average about
0.5 standard deviations higher in neighborliness than NY or LA scenes.
Further dimensions would add more subtlety. Still, we can already see, substantively,
the strongly demarcated local neighborhood cultures of Chicago, just as we saw the strong
cultural distinctions between Toronto and Montreal. Though under Mayor Daley II the city
was substantially transformed in many ways—not only economically—the changes often
focused on the Loop and the North Side, without extending more broadly, which we see in
the concentration of self-expression there but not elsewhere.
Methodologically, the maps show not only how multidimensionality brings more
precise meaning but also how important spatial configurations of scenes can be. An island
of transgression in a sea of tradition is quite different from a cluster of similar scenes
nearby one another. Proximity of clearly demarcated contrasting scenes nearby one
another may intensify cultural opposition and conflict. In the Montreal pattern, by
contrast, extremes of exhibitionism and transgression are less physically distinct and blend
into the more rationalist and utilitarian. We return to this theme in chapter 4.
America as a Cultural Reactor
In a chemical reactor, substances enter in one form and exit in another. Iron and sulfide go
in, iron sulfide comes out. The most common chemical reactions help generate our typical
environments, the air we breathe, the water we drink, the food we eat. In the lab, however,
chemists can generate compounds that could scarcely occur in most places on earth. But
these might be the stuff of everyday normality in the center of the sun or on some far-off
pulsar, not to mention at the bottom of the sea or in the depths of a volcano.
Think of America as a kind of cultural reactor. There are certain typical combinations of
experiences, ambitions, ideals, hopes, meanings we are likely to find wherever we go,
much like most anywhere on earth there is going to be air and water. At the same time,
while some combinations might be normal, they are not necessarily normative. People in
different regions, different cities, different neighborhoods can experiment with
alternatives, and have often spent centuries doing so. They create scenes with their own
logics, their own rules of the game. These can differ sharply from typical cultural patterns,
much like how even on earth chemical reactions can occur under the ocean, where most
organisms live, that might seem strange and unusual to us landlubbers. But these create
their own unique local habitats in which certain specialized types of animals thrive. In a
similar way, we could think of the ward boss as a social type that, like the great coral
reefs, only thrives in certain scenes—in Chicago but not in Los Angeles, for instance.
The Typical American Scene: Gemeinschaft and Gesellschaft
The great late-nineteenth-century German sociologist Ferdinand Tönnies is one of the
main sources of a classical contrast in modern social thought; Simmel, Wirth, and others
extended his ideas. They all contrasted the close-knit village with the anonymous city.
Tönnies called the former Gemeinschaft, or “community,” and the latter Gesellschaft, or
“society.” “Community” is the rural world of folk culture, intimate friendship, extended
family, common understanding, warmth, intimacy, and fellowship. “Society” is the world
of the distant, unfeeling state, the ruthlessly efficient corporation, the impersonal and
heartless laboratory, individualism, and the temptations of high fashion and libertinism.
We call this pattern of scene dimensions, following Tönnies, Communitarianism versus
Urbanity, though sometimes we use the German Gemeinschaft and Gesellschaft. The
communitarian end of this complex of dimensions features neighborliness, formality,
tradition, and charisma.10 Churches are strongly connected with this pattern of
dimensions, with Baptist and Methodist denominations showing the strongest correlations.
Public libraries and fishing lakes are also correlated with this scene. Less communitarian
areas have fewer of these types of amenities, and rationalism, utilitarianism,
corporateness, transgression, and glamour are (relatively) strong. Here, items such as fast
food restaurants, travel agencies, beauty salons, computer programmers, health clubs,
coffeehouses, department stores, software publishers, book dealers, R&D firms, technical
consulting services, and ethnic restaurants are more likely to be present.
Communitarianism/Urbanity in fact accounts for approximately 44 percent of the
country’s total variance in scenes. That is, nearly half the time the strongest difference
between the styles of life in one place and another will be in terms of the degree to which
it feels more or less communitarian. In general, Communitarianism is strongest in the
South and Midwest, while the Northeast and West have more Urbanity scenes.
The Cultural Crucible of Chicago
The Gemeinschaft-Gesellschaft complex captures the most common combinations of
scene dimensions in the United States. But what happens if we leave the familiarity of the
typical and dive deep into the ocean, looking for the social equivalent of manganese
nodules, and their locally unique habitats? To capture how much the same dimensions
overlap in different places, consider figure 3.7.
Figure 3.7
This figure shows Pearson correlations of the YP charisma performance score with five other YP performance scores,
within New York, Chicago, and Los Angeles.
Box 3.11 Gemeinschaft and Gesellschaft
All intimate, private, and exclusive living together, so we discover, is understood as life in Gemeinschaft
(community). Gesellschaft (society) is public life—it is the world itself. In Gemeinschaft with one’s family,
one lives from birth on, bound to it in weal and woe. One goes into Gesellschaft as one goes into a strange
country. . . . There exists a Gemeinschaft of language, of folkways or mores, or of beliefs; but, by way of
contrast, Gesellschaft exists in the realm of business, travel, or sciences. . . . Gemeinschaft is old;
Gesellschaft is new as a name as well as a phenomenon. . . . All praise of rural life has pointed out that the
Gemeinschaft among people is stronger there and more alive. . . . Gesellschaft is transitory and superficial.
Accordingly, Gemeinschaft should be understood as a living organism, Gesellschaft as a mechanical
aggregate and artificial.
In the same way as the individual natural will evolves into pure thinking and rational will, which tends to
dissolve and subjugate its predecessors, the original collective forms of Gemeinschaft have developed into
Gesellschaft and the rational will of the Gesellschaft. In the course of history, folk culture has given rise to
the civilization of the state. . . .
The state, as the reason of Gesellschaft, should decide to destroy Gesellschaft or at least to reform or
renew it. The success of such attempts is highly improbable. . . .
[The metropolis] is the essence not only of a national Gesellschaft, but contains representatives from a
whole group of nations, i.e., of the world. In the metropolis, money and capital are unlimited and almighty.
It is able to produce and supply goods and science for the entire earth as well as laws and public opinion for
all nations.
— Ferdinand Tönnies, Community and Society (2011, 34–35, 223–21)
This figure shows the correlations of charisma with several other scene dimensions
within Los Angeles, Chicago, and New York. To read them, the key is to compare the bars
for each city. For instance, the Chicago bar above neighborliness is around 0.7. This
means that among the roughly 200 zip codes within Cook County, if you come across a
scene that evinces neighborliness, it will also very likely project the feeling that charisma
is an important basis of authority—picture an alderman shaking hands with local notables
as church lets out. Charisma in Chicago is also strongly correlated with egalitarianism and
tradition, but not with glamour and self-expression.
New York and Los Angeles combine charisma with the other dimensions in strikingly
different ways. The bars for correlations of tradition and egalitarianism with charisma in
Los Angeles are near 0, and much lower in New York than they are in Chicago. In these
coastal cities charisma is more often linked with self-expression and glamour than in
Chicago. For instance, the correlation of self-expression with charisma is nearly 0.5 in
New York and LA, compared to below 0.1 in Chicago. And the correlation of glamour
with charisma in LA is over 0.35 but negative in Chicago. These are striking local
variations in the foundations of charisma.
These scenic differences reflect the different amenity mixes that produce charisma in
the three cities. In Chicago, the 30 zip codes that most strongly feature charisma (the ones
with the highest charisma performance score) average over 17 religious organizations and
almost 1 park and playground per zip code; they are mostly located outside of the Loop,
on the South Side and in the inner suburbs. By contrast, the city’s zip codes that specialize
in glamour are more likely to be located in the Loop and in ritzy neighborhoods like the
Gold Coast or Lakeview. On the other hand, New York and LA’s top-performing zip codes
on charisma average fewer religious organizations (13 and 11, respectively) and under 0.3
parks and playgrounds. They are usually more glamorous. Chelsea features charisma most
strongly in New York and has over 100 fashion designers; LA’s top zip codes for charisma
include several zip codes on the South Side with heavy concentrations of churches, but
these are outnumbered by others in places like downtown and Beverley Hills (90210).
Indeed, the top 30 zip codes for charisma in LA average over 9 fashion designers, and
New York’s around 6. Chicago’s charisma by contrast doesn’t come much from fashion:
its top 30 zip codes on charismatic performance average under 1 fashion designer.
Box 3.12 Chicago: Don’t Make No Waves
Daley’s political style is also affected by his parochialism. He has never left Bridgeport. He conceives his
city and world as a series of Bridgeports—communities in which God-fearing, decent, hardworking people
strive to keep the community stable, hold onto the values of their fathers, and fulfill their obligations as
citizens to the neighborhood, the polis, and the nation. Thus, men in politics should be active in the
neighborhood, should concern themselves with those in need in the community, and should stay out of
other neighborhoods, where the people of those neighborhoods should deal with their own problems in
their own way. The world is a Great Neighborhood made up of diverse peoples, each with their own
cultures and customs.
— Milton Rakove, Don’t Make No Waves, Don’t Back No Losers (1975, 63)
In New York and Los Angeles, glamour and charisma often overlap; the Hollywood
hero, music maven, and fashion icon make for charismatic scenes. In Chicago, glamour
and charisma are more often distinct; charisma comes from the community and religious
leaders. Charisma is present in all three cities’ scenes. But when combined with selfexpression and glamour it makes one scene, and when combined with neighborliness and
egalitarianism it makes another. In one, fans, paparazzi, and entourages follow shining
stars on red carpets; in the other, friends, neighbors, and co-ethnics look to the clout of
community leaders, “big men” who have the “juice” to get you a job downtown or a break
on some pesky city ordinance.
This “Chicago molecule” of charisma, tradition, neighborliness, and egalitarianism
(CTN2E2?) was forged in the heat of unique historical experiences, just as certain chemical
compounds only occur in certain geological circumstances. Crucial is the fact that Chicago
is the only large US city with a predominantly Catholic tradition. Recall from above how
many Catholic churches the typical zip code in Chicago has. The parish schools and
churches reinforced the neighborhood community, heightened by the Irish Catholic
political leadership. While New York and Los Angeles have legal arrangements like large
electoral districts created to undermine neighborhood autonomy, Chicago has 50 small
wards where aldermen hold neighborhood parades, for example, on Saint Patrick’s Day,
and more neighborhood festivals than any other US city. Clark’s manuscript in progress,
Trees and Real Violins, a multidecade ethnography and oral history of Chicago from Daley
I to Daley II, studies these special features of Chicago life and politics in further detail.
Conclusion: Scenes Differ from Place to Place, but Do These Differences
Make a Difference?
We could go on in this way further, but for the moment let us resist that temptation to ask
if these scene and amenity patterns matter. Perhaps these aesthetic differences are simply
outcomes of more familiar social science distinctions, like wealth, race, education, or
national origin. If this were so, then all this talk about meaning, this categorizing and
recategorizing of familiar terrain in cultural terms, would be close to pointless, and not
just that—it would be a distraction from the real forces that make the social world go
round.
This is in part a methodological question, about whether the performance scores are, to
use the statistical term, genuinely independent variables. We show how important they can
be in the next three chapters on the economy, residential patterns, and politics. Chapter 8
digs more deeply into the question of what variables most strongly predict what scenes,
and notes that only a small amount of the variation in scenes is explained by variables like
income, education, and race.
More substantively, it is all well and good to describe the landscape as a scenescape, to
see in aesthetic and lifestyle terms that which we usually see in business or political or
demographic terms. But we need to know if these scene differences, to adapt a phrase
from William James, make a difference, for real people, making real decisions that deeply
affect them. Does the fact that one scene rather than another is in one place rather than
another reveal patterns of human conduct that would be otherwise inaccessible?
The next three chapters elaborate answers to this question. We start with conduct in an
arena of life that just about everybody would agree matters a great deal. This is the realm
of business and economics, money and jobs, capital and labor. Do scenes have a part to
play in this realm? The answer is yes. But to see how and why this is so, we need to go
back to the basics of classical theories of economic growth and think anew about how the
cultural character of a locale could be a growth factor somehow on par with the more
familiar factors of land, labor, and capital.
4
Back to the Land, On to the Scene
How Scenes Drive Economic Development
This chapter shows how scenes are factors of production; they are key determinants of
economic success or failure. Even if labor and capital dominate much of economic theory,
these do not explain specifics of why, or especially where, growth occurs. The chapter
comes in three major sections.
The first, on concepts and theory, traces an intellectual movement from “land” as the
physical gifts of nature to “scene” as the cultural and aesthetic characteristics of a locale.
The second articulates several propositions about how variations in scenes should bring
variations in economic growth. And the third tests these propositions by joining the scenes
measures we surveyed in chapter 3 with economic data on jobs, wages, rents, population,
patents, human capital, and more.
While we investigate several specific hypotheses about how the characteristics of the
scenescape relate to economic growth, they are offered to illustrate a larger point that goes
beyond any one specific finding: Scenes are a “new” classical factor of production that
many of today’s businesses ignore to their peril. If for some businesses (like farming) the
qualities of the soil are critical for success or failure, for others (like software firms) the
qualities of the scene where one operates are similarly crucial. To show this, we join
scenes measures with classic variables from economics and geography, revealing how
scenes can substantially influence local economic performance. While many “know” that
scenes are key factors of production, including them in quantitative models shows how
their economic contributions are more than anecdotal.
The Disappearance, Reappearance, and Transformation of “Land”
Classics help identify fundamental assumptions and imagine alternatives. Key classics of
modern social and economic thought in particular often reveal a picture of the world
opaque to the links between scenes and economic growth. But they also suggest why, and
how, to realign our conceptual grid to include scenes more clearly.
Box 4.1 Consecrating a Commercial Society
By what a frugal man annually saves, he not only affords maintenance to an additional number of
productive hands, for that or the ensuing year, but, like the founder of a public workhouse, he establishes as
it were a perpetual fund for the maintenance of an equal number in all times to come. . . .
The prodigal perverts it in this manner. By not confining his expense within his income, he encroaches
upon his capital. Like him who perverts the revenues of some pious foundation to profane purposes, he
pays the wages of idleness with those funds which the frugality of his forefathers had, as it were,
consecrated to the maintenance of industry.
— Adam Smith, The Wealth of Nations (1776, bk. 2, ch. 3)
The basic plot of the story that follows is the articulation, disappearance, reappearance,
and transformation of “land.” We begin briefly with the classical theorists Adam Smith
and David Ricardo, who first articulated land as a key economic concept. Then we see
how land more or less drops out of the picture for Marx, or is pushed backstage, with big
consequences for later theories, especially of globalization. “Land” starts to creep back in,
in a transformed, culturally infused meaning, with authors like Alfred Marshall, Max
Weber, and Talcott Parsons. Next, the “scene” extends and adds much more concrete
empirical meaning to what Marshall, Weber, and Parsons started.
Factors of Production as Social Theory
Adam Smith’s The Wealth of Nations is not just a classic in economics but also a classic of
modern social thought. Perhaps more than any other book, it defined core aspects of a
modern commercial order. Smith’s pioneering analyses of money and markets, capital
accumulation, and the division of labor surely have much to do with the book’s enduring
power. But rhetoric matters too. Indeed, Smith crafted a kind of sacred language of
commerce. The aristocrat, whose leisure and martial virtues had hitherto been objects of
reverence, becomes a perverse, if in certain ways lovable, profligate. The hard-working,
frugal, entrepreneurial artisans and traders, whose savings lead to the steady accumulation
of capital that calls forth the productive capacities of the nation, take the spotlight on the
stage of history.
The Wealth of Nations is in many ways like the sociological equivalent of early
astronomy. Instead of looking to the sky and constructing order from randomness, here we
see a framework to reinterpret the social world. There is a socio-logic to the rise and fall
of business sectors, movements of prices, rewards for various types of work, productivities
of different workplaces, and conflicts between classes.
Smith divided society into three great classes: landlords, workers, and capitalists. This
was based on a theory of the distribution of the “proceeds of labor” that make up “national
wealth”—the total goods and services produced in a given nation. That wealth can go to
profits, to wages, or to rents. Profits are the proceeds of capital, wages of labor, and rents
of land—the three classical “factors of production” (Alfred Marshall, to whom we will
return, and Joseph Schumpeter, added a fourth, known variously by Marshall’s terms
“management” and “business power” or Schumpeter’s “entrepreneurship.”)
On this basis, Smith developed, among other things, a theory of social conflict, based
on the interests of the three great classes and their ability to act on and understand their
interests. For people only familiar with the received view of Smith as Godfather of
Kapitalismus, his theory of social conflict comes as a shock. For, in broadest outlines,
Smith argues that the interests of capital are inherently hostile to the overall good of
society while those of the workers are inherently aligned with those of society. Workers’
main interest is in higher wages, and these, Smith argues, tend to at once signal increasing
productivity and to create the basis for a broadly shared prosperity that places the general
interests of consumers above the particular interests of any given firm or sector. The
owners of capital, by contrast, tend to elevate the interests of producers over those of
consumers to keep profits high, even—or especially—if that means offering lower quality
goods for higher prices. The problem is that owners know and can act on their interests
while workers typically do not and cannot.
Landlords are in a strange middle position for Smith. Their interests ultimately align
with those of the nation and of the workers. “Every increase in the real wealth of the
society, every increase in the quantity of useful labor employed within it, tends indirectly
to raise the real rent of land” (A. Smith 1776, bk. 1, ch. 11). But they tend to misrecognize
those interests. Because they live by sitting back and collecting rent rather than by
constantly scheming up ways to make profits, landlords—“country gentlemen,” as Smith
often calls them—are less likely than are capitalists to take the long view and to lobby for
it in the halls of power, despite their ample time and education. They become blinded by
the allure of renting their land to high-profit businesses and by the cunning rhetoric of the
owners of capital. “It is by this superior knowledge of [the proprietors’] own interest that
they have frequently imposed upon [the country gentleman’s] generosity, and persuaded
him to give up both his own interest and that of the public, from a very simple but honest
conviction, that their interest, and not his, was the interest of the public” (ibid.).
Box 4.2 Adam Smith: Conflict Theorist
The interest of [those who live by rent] . . . is strictly and inseparably connected with the general interest of
the society. . . . They are, indeed, too often defective in . . . tolerable knowledge [of their interests]. They
are the only one of the three orders whose revenue costs them neither labor nor care, but comes to them, as
it were, of its own accord, and independent of any plan or project of their own. That indolence, which is the
natural effect of the ease and security of their situation, renders them too often, not only ignorant, but
incapable of that application of mind which is necessary in order to foresee and understand the
consequences of any public regulation.
The interest of the second order, that of those who live by wages, is as strictly connected with the interest
of the society as that of the first. . . . But though the interest of the laborer is strictly connected with that of
the society, he is incapable either of comprehending that interest, or of understanding its connection with
his own. His condition leaves him no time to receive the necessary information, and his education and
habits are commonly such as to render him unfit to judge even though he was fully informed. In the public
deliberations, therefore, his voice is little heard and less regarded, except upon some particular occasions,
when his clamor is animated, set on, and supported by his employers, not for his, but their own particular
purposes.
His employers constitute the third order, that of those who live by profit. . . . But the rate of profit does
not, like rent and wages, rise with the prosperity, and fall with the declension of the society. . . . The interest
of this third order, therefore, has not the same connection with the general interest of the society as that of
the other two. . . . As during their whole lives they are engaged in plans and projects, [merchants and
master manufacturers] have frequently more acuteness of understanding than the greater part of country
gentlemen. As their thoughts, however, are commonly exercised rather about the interest of their own
particular branch of business, than about that of the society, their judgment, even when given with the
greatest candor (which it has not been upon every occasion) is much more to be depended upon with regard
to the former of those two objects, than with regard to the latter. . . . The proposal of any new law or
regulation of commerce which comes from this order, ought always to be listened to with great precaution,
and ought never to be adopted till after having been long and carefully examined, not only with the most
scrupulous, but with the most suspicious attention.
— Adam Smith, The Wealth of Nations (1776, bk. 1, ch. 11)
The result is that for Smith landholders tend in the end to align, against their own
interests, with the owners of capital to keep down the wages of labor. This political
alignment from Smith’s perspective in turn would explain the historical association of
landlords with the forces arrayed against the public interest in broad-based growth.
However, by articulating how this coalition is based on misrecognizing the landlord’s true
interests, and thus the role of land in generating the wealth of nations, Smith also suggests
that a fuller accounting of land as a factor of production might produce a broader
assessment of its significance.
Land as the Value of Place
To do so, we turn to others who built on the foundations Smith laid, starting (briefly) with
another great early modern economic and social thinker, David Ricardo. The details and
intricacies of Ricardo’s theory need not detain us, such as his idea that rent is determined
by the “last” plot of land brought into cultivation.1 More important is the underlying
intuitive logic.
Take two farmers. Each works about the same amount of time per day and has more or
less the same set of tools. That is, labor and capital are the same. Put Farmer #1 on rich,
fertile soil and Farmer #2 on dry, cracked soil. Farmer #1 will be more productive. That
added value is what land contributes as a factor of production, and when land is scarce,
that value can generate a rent.
This is an intuitive, not particularly “deep” observation, though Ricardo did derive
some counterintuitive and far-ranging consequences from it. What is important in the
present context, however, is that the concept of land focuses analytical attention to the
specific characteristics of a locality—at first how fertile the soil is, but also air quality,
sunlight, and then qualities like distance and access to markets and suppliers (via, for
instance, waterways or railroads). Including land as a factor of production in this way
naturally puts on the analytical radar questions about how local area characteristics
influence economic success or failure.
The Eclipse of Land as the Eclipse of Distance
Marx wrote his masterwork, Capital, after years of reading Smith and Ricardo, among
others, while sitting in the British Museum Reading Room in London. It is a book that
defies summary. This is not least because, in contrast to the straightforward style of his
Anglophone predecessors, there are multiple levels of irony and bitter humor at work in
Capital, which is as much a literary work as a work of political economy.
Be that as it may, when one turns to Capital after Smith and Ricardo, one is struck by
the fact that land has for the most part dropped out of the story. There is almost no
discussion of rent and land in the first two (massive) volumes of the book. The topic does
arise in the third volume, which is a collection of Marx’s unpublished notes compiled (and
often extensively edited) by Engels after the death of the Master. And Marx further
discusses land and rent in significant detail in Theories of Surplus Value, which is mostly a
collection of notes about classical political economists (like Smith and Ricardo) that was
not published in its entirety until 1956. Marx, that is, was never able in his lifetime to
integrate a theory of land and rent with his more famous discussions of capital and labor. It
is perhaps telling that while the size of the literature on Marx may rival that of the Bible
and Shakespeare, a recent survey of articles on Marx’s theory of rent by economist Miguel
Ramirez (2009) turned up only a dozen or so items. Geographers, most notably David
Harvey in Limits to Capital, have endeavored to extend Marx’s thoughts on the topic, but
even Harvey calls Marx’s ideas “tentative thoughts set down in the process of discovery”
(1982, 330).2
With land offstage, capital and labor, aka bourgeoisie and proletariat, steal the show. As
Marx describes it in The German Ideology, the precapitalist, premodern world was one of
rich diversity, filled with barons, knights, monks, bishops, kings, artisans, shopkeepers,
traders, troubadours, and much, much more. While social conflict was rampant, it was also
complex, not reducible to any single opposition.
The capitalist order simplifies all of this. Capitalism acts like a solvent, clearing away
mystical distinctions, antique metaphysics, and hoary sentimentality. Everything must
become capital, and capital must mediate everything.3 All that is left is capital—and what
it cannot do without in order to put itself into motion, labor. The ensuing clash between
bourgeois and proletariat, in which capital aims to transform humanity’s most essential
capacity, labor, into a tool for its own purposes, brings the class struggle that has defined
the history of all hitherto existing history to its sharpest, culminating point.
This is already a strong contrast to Smith, who was most at home in a rich and diverse
social environment. The Wealth of Nations gives pride of place to the butcher, the brewer,
and the baker, staple figures in a small town and dense urban environment. And Smith
thought the life of the farmer, in the country air and with his property under his own gaze,
the ideal to which any healthy person would be drawn. The merchants and great
manufacturers, though admirable in their own way, nevertheless provoked in Smith a kind
of anxiety, in no small measure because they were untethered to any particular place, at a
distance from their property and fellows, disconnected from the local habits and customs
of those with whom they worked.
Marx likely saw this as a bit of sentimentality on Smith’s part. Merchants and the
master industrialists represented the future, a future that was black and white. As Marx
had already made clear in his early Economic and Philosophic Manuscripts, the moral and
economic significance of rich cultural diversity—embodied (for Smith) in local shop
owners or the country gentlemen—is the stuff of feudalism. It would not last against the
onslaught of capital. “Large landed property, as we see in England, has already cast off its
feudal character and adopted an industrial character insofar as it is aiming to make as
much money as possible” (Marx [1844] 1959). And so, the third principal character in
Smith’s theory of society is nudged ever closer to the cliff.
To be sure, Marx had his own, powerful reasons for downplaying land. There were
economic-technological reasons. If land seemed somehow different from industry, this
was primarily because capital had been, and still was in Marx’s day, applied less
extensively to agriculture. But as agricultural technology improved, it would make the
physical qualities of the earth seem less gifts of nature that cause local disturbances to the
pure operations of capital (Marx 1967, 3:861) and more objects that bend to human
technological mastery, that is, capital. Land’s scarcity and qualities would thus matter less
as capital improvements continued (3:760, 765).4
There were also political reasons. A three-way contest/interaction is far more complex
than a one-on-one showdown. Leaving land as an independent factor means leaving the
landlords as an independent social base of power, making it far harder to view social
tensions as a kind of O.K. Corral standoff between bourgeoisie and proletariat. Landlords,
Marx wrote, were an “alien force” that owed its existence primarily to outdated feudal
property rights that continued due to power, and only power.5 In fact, revenues from land
are parasitic on the activities of parasites, that is, capitalists. While capitalists at least
exercise rationality with energetic coldness in exploiting the workers, the value in land
comes from leeching from the leeches, skimming the top off the “work” of capitalists,
which is a form of work that for Marx barely deserves the name.
Box 4.3 A Conversation between a Landlord and a Capitalist
Just as your ownership of one condition of production capital, materialized labor, enables you to
appropriate a certain quantity of unpaid labor from the workers, so my ownership of the other condition of
production, the land, etc., enables me to intercept and divert away from you and the entire capitalist class,
that part of unpaid labor which is excessive to your average profit. Your law will have it that under normal
circumstances, capitals of equal size appropriate equal quantities of unpaid labor and you capitalists can
force each other into this position by competition among yourselves. Well. I happen to be applying this law
to you. . . . But the law has nothing to do with the excess of unpaid labor which you have “produced” over
the normal quota. Who is going to prevent me from appropriating this “excess”? Why should I act
according to your custom and throw it into the common pot of capital to be shared out among the capitalist
class[?] . . . I am not a capitalist. The conditions of production which I allow you to utilize is not
materialized labor but a natural phenomenon. Can you manufacture land or water or mines or coal pits?
Certainly not.
— Karl Marx, Theories of Surplus Value ([1862–1863] 1968, 41)
Philosophical reasons were important as well, even if they are less discussed in the
political-economic histories of Marx’s ideas. Marx was after all a German philosopher,
deeply influenced by Hegel. For metaphysical reasons, he needed communism to be a
dialectical synthesis of opposites. A unity-out-of-opposites cannot be derived from three
terms, however much one tries. There needs to be two polarities, one that is “everything,”
one that is “nothing.”6
So land made its way out the door. What happens when land drops out of our core set of
social science concepts? We are left with capital and labor. Once they are unmoored from
the qualities of any specific location, both quickly become standardized, abstract, and
placeless. Capital flows to wherever wages are lowest; labor moves to high wages. Labor
itself becomes a homogeneous block, undifferentiated by local heritage, customs, and
habits, whose productivity can be measured on a single standard based on “socially
necessary labor time,” that is, however long it takes the average person to do a given type
of work. This makes all work at all places comparable on a single unvarying scale. Capital
too becomes standardized. A factory is a factory is a factory, generating a certain output
wherever it is, independent of what and who surrounds it.
Now it is possible that Marx meant much of this to be taken ironically. A bitter joke
exposing from within the human deformations caused by capitalism, which tricks us into
seeing capital as able to master and render impotent nature, humanity, and culture. This is
the forceful literary interpretation of Capital that Robert Paul Wolff (1998) puts forward in
his Moneybags Should Be So Lucky.
Perhaps so, but many have yet to get the joke. Consider standard interpretations of the
social effects of globalization or the Internet, like the “death of distance” or “the world is
flat” or the “McDonaldization of the world.” The assumption is that since work can be
done equally well from anywhere, it will flow to wherever it can be done most cheaply.
Attachment by people and firms to a particular place is a kind of persistent, stubborn
irrationality, which should eventually give way to more abstract and global standards that
hold everywhere, equally.
This is not just the stuff of the New York Times punditry or prognostications from the
early days of the Internet age. Harvard political theorist Michael Sandel has linked the
flattening of the world to the Marxian picture of global capitalism. This universalizing
tendency, he argues, threatens “the distinctive places and communities that give us our
bearings, that locate us in the world” (Friedman 2005, 236; see box 4.4). Some economic
historians (e.g., Gaffney 2006) have made similar points about the simplifying
consequences of thinking in terms of a “two-factor” world.7
Back to the Land
There is another tradition besides the Marxian one, however, in which land continued to
figure prominently, albeit in a transformed way. It is too rich and complex to detail here,
but we highlight some central points. Two key figures are Alfred Marshall and Max
Weber, whose ideas Talcott Parsons and Neil Smelser joined in a new theory of land in
their Economy and Society.
Box 4.4
Harvard University’s noted political theorist Michael J. Sandel startled me slightly by remarking that the
sort of flattening process that I was describing was actually first identified by Karl Marx and Friedrich
Engels in the Communist Manifesto, published in 1848. . . .
“Marx was one of the first to glimpse the possibility of the world as a global market, uncomplicated by
national boundaries,” Sandel explained. . . . “In the Communist Manifesto, he described capitalism as a
force that would dissolve all feudal, national, and religious identities, giving rise to a universal civilization
governed by market imperatives.” . . .
Indeed, reading the Communist Manifesto today, I am in awe at how incisively Marx detailed the forces
that were flattening the world during the rise of the Industrial Revolution, and how much he foreshadowed
the way these same forces would keep flattening the world right up to the present. . . .
Sandel told me, “You are arguing something similar [to Marx]. What you are arguing is that
developments in information technology are enabling companies to squeeze out all the inefficiencies and
friction from their markets and business operations. That is what your notion of ‘flattening’ really means.
But a flat, frictionless world is a mixed blessing. It may, as you suggest, be good for global business. Or it
may, as Marx believed, augur well for a proletarian revolution. But it may also pose a threat to the
distinctive places and communities that give us our bearings, that locate us in the world.”
— Thomas Friedman, The World Is Flat (2005, 235–36)
Parsons was a giant in mid-twentieth-century sociology, even if his star has waned. One
of his major preoccupations was to integrate economics and sociology into a general
system that would preserve a distinct place for each. To this end, his first major work, The
Structure of Social Action ([1937] 1967), joined the thought of two economists, Alfred
Marshall and Vilfredo Pareto, with that of two sociologists, Max Weber and Émile
Durkheim, neither of whom had been much read before that in North America. Parsons
went on to translate and introduce to an American audience Weber’s classic, The
Protestant Ethic and the Spirit of Capitalism.
In 1956, with his student Neil Smelser, Parsons published Economy and Society, which
returned to the links between general social theory and economic theory. The primary goal
of the book was to situate the problems of economics—price, distribution, growth, and so
forth—within a broader framework. This would highlight more distinctly the specific
problems of the economist. And, perhaps more importantly, the aim was to provide a way
to systematically investigate the many noneconomic factors that influence the economy
“from the outside,” as it were, and which economies influences in turn—power politics,
legal regulations, and, above all, cultural norms.
Writing at the end of his career, Parsons in his American Society (published
posthumously in 2006) observed that the major “bombshell” of Economy and Society was
its interpretation of the concept of land. Parsons and Smelser advanced this interpretation
through close attention to the work of Marshall and Weber. The key similarity in Marshall
and Weber is a deep sensitivity to the fateful economic consequences of what the classical
economists called habits and custom. We would now call that culture. This idea is present
but downplayed in Smith, Ricardo, and also Marx. Marshall and Weber give it pride of
place.
That Weber would be a key source in drawing the connection between culture and land
is no accident. Weber, a polymath of the first order, was first and foremost an expert in
agrarian economics and legal history. Land and the historically and socially shifting
meanings of property were always in his intellectual crosshairs.
While Weber’s main argument in The Protestant Ethic is one of the most famous in the
history of modern social theory, its link to the concept of land is not immediately apparent,
and much of the originality of Parsons and Smelser’s argument lies in making the
connection. The key linkage lies in the fact that while both the Puritan commitment to
work in a calling and the gifts of nature (like waterfalls and fertile soil) are not created for
economic reasons (like wages or profits), they both generate tremendous economic
consequences. How?
For the Calvinist, there are a fixed number of slots among God’s elect. Precisely who
will occupy those slots is predestined. Being all-powerful and all-knowing, God already
knows who is in and who is out. But to know if you yourself are among the elect? Being
finite and mortal, you cannot. What can you do to earn a place? Nothing.
Calvinists thus found themselves in a terrific psychological predicament. Their solution
was, in its own way, ingenious; it amounted to shifting the question of election into the
subjunctive, so to speak. If you were among the saved, then surely your life would testify
to your faith, wholly and completely, in all your thoughts, feelings, and actions, without
any remainder. While there may be nothing you can do to force your way into heaven, you
can look within yourself for signs that you already are one of the elect.
Box 4.5 Puritan Self-Fashioning
14 June 1595. My negligence is not calling upon God before I went to the chapel, and the little desire I had
there to call on God, and my drowsiness in God’s service. My sins even through the whole day, being
Sunday: (1) my negligence aforesaid, (2) my hearing of the sermon without that sense which I should have
had, (2) [sic] in not praying God to bless it to me afterward, (3) in not talking of good things at dinner being
the posteriorums day, (4) in the immoderate use of God’s creatures, (5) in sleeping immediately after
dinner, (6) in not preparing me to sermon till it tolled, (7) in sluggish hearing of God’s words, and that for
my great dinner, (8) in hearing another sermon sluggishly, (9) in returning home and omitting our
repetitions of sermons, by reason that my countryman Eubank was with me, (11) [sic] in not exhorting him
to any good thing, (2) in not going to evening prayers, (13) in supping liberally, never remembering our
poor brethren, (14) in not taking order to give the poor women somewhat at 7 o’clock, (15) my dullness in
stirring of my brother to Christian meditations, (16) my want of affections in hearing the sermons repeated,
(17), my sluggishness in prayer, and thus sin I daily against thee, O Lord
— Samuel Ward, diary excerpt, in Margo Todd (1992, 236)
What followed was intense scrutiny of the self. One had to penetrate deep within,
scouring the soul for any signs of evil, in the hopes of making oneself utterly transparent
before God. It was in this context that diary keeping first emerged as an active practice of
self-inspection.
But inwardness was not enough. Faith had to shine through in all your activities,
including the most mundane, like the day-to-day tasks of earning a living. This radically
transformed the nature of work, from a means to some other end (like survival or pleasure)
to a vocation, worthwhile in itself. A member of the elect would not spend the bulk of his
hours doing meaningless tasks; he would throw himself into his work with all his heart; he
would be as scrupulous and trustworthy in business as at home; he would not covet profits
for personal glorification and immediate enjoyment but would deny present pleasures by
saving for the future.
In so doing, he would become a success in business, even while remaining true to
Christian injunctions against conspicuous displays of wealth. While business success
would put him in control over large sums of money, this in itself was not a problem. If
God had a choice between two souls, one whose business had become successful through
honest hard work, and another whose had failed from the opposite, whom would He have
chosen? The question answers itself.
Economic success in this way becomes a sign—but not a cause—of election. And here
is the connection to the concept of land. A waterfall was not made because of the profits to
be had in electricity generation; it is a free gift of nature. Calvinists are similarly devoted
to their work largely independent of economic considerations like wages and profit. Their
commitment to work as a calling is a free gift, not of nature but of faith. All the same, it
promises a bonus, a surplus, to anybody for whom they work.
From the perspective of a firm, therefore, places infused with Calvinist theology
become very much analogous to good soil. If you had a choice of two locations to start a
business, one animated by the idea that doing one’s job well is a task set by God, and
another less animated in this way, which would you choose? Once again, the question
answers itself.
Though Weber did not explicitly take the next step of not only connecting land to
culture but also connecting culture to rent, Marshall did. He paved the way for breaking
the classical identification of rent with the literal God- (or Nature-)given earth via ideas
like “quasi-rent” and “rent of ability.” The key conceptual innovation was to treat rent as
an analytical element present in all objects of value, rather than as strictly identical with
the physical earth: “Even the rent of land is seen, not as a thing by itself, but as the leading
species of a large genus” (Marshall 1892).
Building out from this insight, Marshall developed a far-reaching account of various
types of rent. Quasi-rents come from various permanent human improvements to nature,
such as better farmhouses, plumbing, irrigation, and the like. Though over the long term
such improvements may be due to the profits they generate (this is why they are only
“quasi” rents), in the short and middle terms, they are for all intents and purposes like
good soil and air; they provide a bonus to all who work in their midst, and their owners
can therefore charge a rent for access to this bounty.
Box 4.6 Rent as an Analytical Category
There is an element of true rent in the composite product that is commonly called wages, an element of true
earnings in what is commonly called rent and so on. [We] have learnt in short to follow the example of the
chemist who seeks for the true properties of each element, and who is thus prepared to deal with the
common oxygen or soda of commerce, though containing admixtures of other elements.
— Alfred Marshall, Principles of Economics (1892, bk. 5, ch. 9, par. 4)
Rent of ability is just as important. One of Marshall’s examples comes from theater.
Actors may cultivate their theatrical talents for all sorts of reasons, perhaps only a small
fraction of which have to do with the wages which they earn from those talents. But if for
some reason demand for theater rises substantially—from, say, a general societal increase
in education or affluence—actors will be able to reap the rewards of their gifts. There are
now dozens of shows around town and only so many people with the ability to star in
them! This is not different in any essential way from what happens when some new
technological innovation renders the minerals buried in some plot of land suddenly
valuable, and makes the owners of that land wealthy in the process.
While Marshall acknowledged that the “situation value” that some areas have comes
sometimes from developing their surroundings with a view to profits—think of planned
towns built expressly to make a profit on proximity to a factory or waterfront—the bulk of
that value is what he called “public value.” This is locational value that comes not from
any direct effort to acquire such value but rather from the public and quasi-public goods
nearby. If the value of your home goes up $100 when a sushi restaurant opens around the
corner, this is public value—the restaurateurs did not go into business to raise your home
value, but through their actions they changed the character of your environment, which in
turn would permit you to charge higher rent. Rent, in sum, is not “in” the land but rather is
the economic benefit that accrues indirectly from goods or services not necessarily
generated directly for economic ends. Rent rewards, we might say, the “effortless”
component of our actions, that which we possess and are—hence the connection to
property—without having to strive after it.
A similar sensitivity to locational dynamics fed into Marshall’s pioneering analyses of
industrial districts. It is in this context that he made his famous statement that where
complementary industries colocate there emerges “something in the air” that heightens the
performance of all. Marshall has accordingly become a classic for economic geographers
who study agglomeration effects. The foregoing discussion indicates, however, that these
sorts of agglomeration effects are a special case of something broader and deeper, which
goes beyond direct monetary benefits of concentration or a narrow conception of
creativity as technical innovation: breathing the “air” of a distinctive place inspires a
characteristic mode of existence and style of interaction, which imbues actions there with
heightened meaning and importance. Such scenes, even the most traditional, are creative
accomplishments that can draw people into the dramas they make possible and fill their
surroundings with enhanced value.
Parsons and Smelser extended and joined all these ideas from Weber and Marshall by
dividing the concept of land into three: physical facilities (earth, sun, soil), cultural
facilities (e.g., “state of the art” knowledge and skills), and motivational commitment (like
the Protestant ethic). These are all relatively insensitive, at least in the short term, to price;
they are there regardless of what anybody is willing to pay for them. They vary
considerably by location; some places have more or less of them. And they provide great
advantages to firms and workers who locate near them.
On to the Scene
Think of the economic significance of scenes as an extension and specification of this
Weber-Marshall-Parsons-Smelser tradition. The key idea again is intuitively simple.
Places differ sharply in terms of the opportunities they afford to cultivate certain ranges of
experiences. Such experiences include the kind of impassioned dedication to work
characteristic of Weber’s Puritan.
But the range of possibilities is much greater now than in Weber’s day. There are places
that encourage you to be glamorous, to express your uniqueness, to break normal
standards of appearance, to connect to a tradition, to work hard, to be a good neighbor and
community member, to shop and eat local, to kick back and relax, and more. We can
recognize these intuitively when we walk or bike—or quantitatively stroll—from
neighborhood to neighborhood. And all of these can come in different degrees and
combinations. Hence the 15 dimensions of scenes and the many complexes of these we
have introduced.
With these experiences, as with Weber’s Protestant ethic or Marshall’s public value, we
need not presume that people primarily pursue them for the sake of their economic
consequences (though of course they may do so). There is something attractive in itself in
shining out on the dance floor, playing improvisationally in a jazz club, feeling rooted at
home in a local pub, seeing oneself as connected with others in relations of mutual trust in
a community center or neighborhood parish, and so on. But where certain of these
experiences are strong (“in the air”) and easily available, certain types of firms clearly
have better chances of succeeding—the economic value of a scene derives in no small
measure, that is, from the experiences it creates. For scenes cultivate skills, create
ambiances, and inculcate commitments that may be quite valuable to some types of work.
Box 4.7 From Industrial Districts to Bungalow 8
The Bungalow 8 and the SoHo of the creative industries are the Marshallian industrial districts of the
Industrial Revolution. And they are speaking the same language—there is something “in the air,” as
Marshall put it, these are places where knowledge is exchanged in the most casual but significant
capacities. It isn’t just over social engagements like dinner or power lunches but through music venues,
gallery openings, and DJ nights that real knowledge and collaborations and product review are occurring.
Nightlife is economically meaningful in the creative world. As Quincy Jones explained, “Because it’s
about interacting. People interacting with each other, it’s very important.” And particular places are
especially significant for specific industries. Places like APT and Cielo in the Meat Packing District and
Table 50 and the now-closed CBGB are huge sites for musicians, while the restaurant Indochine is a big
fashion industry hangout. . . . Daniel Jackson, designer and cofounder of Surface to Air, corroborated, “A
Friday night at APT is where you meet someone and work comes out of it.”
— Elizabeth Currid, The Warhol Economy (2007, 95–96)
Six Hypotheses about How Scenes Improve Economic Performance
Take two video game design firms rather than two farmers, and call them Tech Firm #1
and Tech Firm #2. Tech Firm #1 locates in a scene that encourages personal selfexpression, Tech Firm #2 in a scene that does not (as much). Tech Firm #1 is near the
“state of the art” in new ideas, surrounded by an atmosphere that encourages innovation,
not sticking with conventions. This is good soil for a firm that uses such abilities,
commitments, and atmospheres, which it can “rent” when it hires somebody or when it
literally rents an office on the scene. Its video games are better for it.
We could form similar hypotheses for other occupations, like artists. That artist clusters
enhance, at least in more culturally oriented postindustrial economies, the performance of
all sorts of work has been a keynote in several overlapping academic literatures.
Economist Ann Markusen coined the term “the artistic dividend.” She highlights the
prominence of artists in many contemporary workplaces, which increasingly require their
services, such as graphic design, web design, product design, marketing, or advertising
copy (Markusen, Schrock, and Cameron 2004). Similarly, sociologist Richard Lloyd
(2006) argues that artist neighborhoods like Chicago’s Wicker Park play a key role in
cultural production, gathering talent, stimulating new styles, sharing ideas. And one of
Richard Florida’s (2002) central claims in The Rise of the Creative Class is that the
“Bohemian” sensibilities traditionally associated with artists now enhance rather than
undermine workplaces by inculcating habits of experimentation and imagination favored
by the “creative economy” more broadly, beyond artists narrowly construed. Nonartist
“creatives,” he argues, move near and learn from the denizens of Bohemian artist clusters,
who themselves become less hostile to an economic order that now increasingly welcomes
rather than represses them.
Box 4.8
What men want is not so much to get things that they want as it is to have interesting experiences.
— Frank Knight, Risk, Uncertainty, and Profit ([1921] 2000, pt. 2, ch. 3, par. 5)
Box 4.9 Genius vs. Scenius
I was an art student and, like all art students, I was encouraged to believe that there were a few great figures
like Picasso and Kandinsky, Rembrandt and Giotto and so on who sort-of appeared out of nowhere and
produced artistic revolution.
As I looked at art more and more, I discovered that that wasn’t really a true picture. What really
happened was that there was sometimes very fertile scenes involving lots and lots of people—some of them
artists, some of them collectors, some of them curators, thinkers, theorists, people who were fashionable
and knew what the hip things were—all sorts of people who created a kind of ecology of talent. And out of
that ecology arose some wonderful work.
The period that I was particularly interested in, ’round about the Russian revolution, shows this
extremely well. So I thought that originally those few individuals who’d survived in history—in the sort-of
“Great Man” theory of history—they were called “geniuses.” But what I thought was interesting was the
fact that they all came out of a scene that was very fertile and very intelligent.
So I came up with this word “scenius”—and scenius is the intelligence of a whole . . . operation or group
of people. And I think that’s a more useful way to think about culture, actually. I think that—let’s forget the
idea of “genius” for a little while, let’s think about the whole ecology of ideas that give rise to good new
thoughts and good new work.
— Brian Eno in Synthead, “Brian Eno on Genius, and ‘Scenius’” (2009)
Box 4.10
It must be remembered that those who pay the high town rents get in return the amusements and other
advantages of modern town life, which many of them would not be willing to forego for the sake of a much
greater gain than their total rent.
— Alfred Marshall, Principles of Economics (1892, bk. 6, ch. 12, sec. 5)
However powerful these links between artist clusters and broadly shared growth may be
per se, they are likely enhanced by a supportive scene. Take two artists, Artist #1 and
Artist #2. Each works, let us say, about the same number of hours per week and has more
or less the same set of tools (computers, paints, software, etc.). Artist #1 is located in a
thriving scene that encourages spontaneity (individual self-expression), putting on a
stunningly refined show (glamour and formality), and standing out from the crowd
(charisma). Artist #2 is located somewhere where these qualities are muted or even
opposed. Artist #1 is working on fertile artistic ground: in that scene, there is, we might
imagine, an openness to improvisation and risk, an understanding that many ideas don’t
pan out, opportunities for idea and technique sharing, encouragement to rise to the
occasion and produce something grand, a willingness to cast off conventional stereotypes
and return to primal, unvarnished experiences, and much more. This is a scene, we might
hypothesize, encouraging and hospitable to high quality artistic work, not to mention the
attendant “dividends” it may provide for others.
In both cases, the tech firm or artist on more fertile soil will generate significant
economic returns. By contrast, tech firms or artists on soil not conducive to their work
would not, or at any rate would do so to a lesser extent. But in this case “soil” is not dirt
but life in the scene.
In these examples, we are hypothesizing that within different scenic contexts, the
economic impacts of other variables should change. Here are three specific empirical
generalizations that follow (three more come below): (1) When located in scenes that
more strongly support self-expression, firms producing innovative products, like advanced
technology, should be associated with economic growth; when located in scenes that
oppose self-expression, their association with economic growth should be weaker. (2)
General economic growth, as well as growth in the broader creative class, should be
stronger when artists are located in more self-expressive, glamorous, and charismatic
scenes, but weaker when they are located in scenes that run counter to these dimensions.
(3) Not only rent but many types of economic growth indicators should rise more in these
(self-expressive, glamorous) scenes.
The Economic Impacts of Scenes Are Altered by Their Surroundings
We could just as well theorize not only about how scenes alter the economic effects of
other variables but also about how the economic impacts of scenes change depending on
their surroundings, as Marshall’s ideas about “situation value” would imply. Consider
Bohemia as an illustration of these situational shifts. Bohemia is a useful concept in this
connection because of its strong historical linkage to concrete places. Think of the Latin
Quarter, Greenwich Village, Haight-Ashbury, or, more recently, Parkdale in Toronto or
Pilsen in Chicago. These are all specific neighborhoods, which invite those who enter to
think of themselves as a struggling but elite cadre of nonconformists, thinking thoughts,
feeling feelings, experiencing experiences that would be out of bounds for “regular”
people.
Yet classical Bohemias are not isolated neighborhoods. They have often been at their
peaks at specific moments in the histories of their surrounding cities. In fact, the wider
metro areas of which Bohemias are a part have in many cases not been very Bohemian.
The Latin Quarter in the 1840s stood out because the rest of Paris provided fewer
opportunities for concentrated and public experiences of self-expression. Paris Bohemia
was at its strongest when Louis-Philipe was at his most repressive. Wicker Park in the
1990s existed within a Chicago that until very recently was dominated by the social life
that took place in ethnic churches and supported the political machine. Toronto’s first
Bohemian stirrings came in the Yorkville neighborhood in the late 1960s and early 1970s,
stamped by the moralistic environment of “Toronto the Good” in which, as Ernest
Hemingway described it, “85% of the inmates attend a Protestant Church on Sunday”
(Lemon 1985, 57).
Spatial boundaries, that is, intensify symbolic boundaries. To set foot inside a Bohemian
quarter and to feel at home is to mark yourself off against the squares over there in their
cubicles. By contrast, if an entire metro area were “Bohemian,” then this boundary work
would be much harder. If your mother enjoys punk music and alternative theater, your
boss plays in a psychedelic band, and your neighbors all smoke marijuana, there is less to
rebel against. Bohemia becomes Neo-Bohemia, ordinary, not a beacon for the misfits of
the world.
Local authenticity is another key dimension of a scene that stresses sensitivity to the
surrounding local context. Indeed, the very attraction of “the local” is that one expects to
find something here that you can get only here, something distinctive, not (yet?)
homogenized by the standardizing forces of global capitalism. Thus sociologist Sharon
Zukin has linked local authenticity to neighborhood growth by specifically highlighting
the case of New York’s Lower East Side. Local charm attracts persons dissatisfied by an
increasingly McDonaldized and uniform world culture, and spurs demand for local
products and services from fruit and vegetable stands to independent record stores to the
local cafe.
In what situations would the allures of local authenticity be especially strong? Consider
two possibilities. A first has to do with what the people in the scene spend their time
doing. Specifically, do they walk or drive? Why should this matter? Walking sensitizes
people to their environments; it slows the pace of life. On a walk, you can relatively easily
greet and patronize the local grocer, wave to or stop for a drink with the cafe regulars, and
stroll through the neighborhood flea market. All this is hard to do at 60 mph. That is, local
authenticity may become more attractive as an alternative to globalized high-speed
modernity when coupled with the more relaxed pace implied by walking. A hypothesis
results: growth should be stronger, especially among firms which are local themselves, in
locally authentic scenes where there are more rather than fewer people who regularly
walk.
Box 4.11
Bohemia is always yesterday.
— Malcolm Cowley, Greenwich Village in the 1920’s: Exile’s Return, a Literary Odyssey of the 1920’s
(1964, 62)
In the dime stores and bus stations / People talk of situations / Read books, repeat quotations / Draw
conclusions on the wall / Some speak of the future / My love she speaks softly / She knows there’s no
success like failure / And that failure’s no success at all
— Bob Dylan, “Love Minus Zero / No Limit” (2004)
Box 4.12
A former poet laureate of Toronto, Pier Giorgio Di Cicco, said in a 2004 speech that the city is falling in
love with itself “as a haven against, and a cultural blueprint against, globalization, and as a great
experiment in the rehumanization of contemporary life. There is an excitement that carries its own
momentum.” Toronto is always changing, always reinventing its parts, working from a Victorian base that
serves as a kind of scaffolding for all the new people, with their new ways of doing things, who have
changed and continue to change the city into something bigger and more interesting.
I undertook many of the walks in this book either alone or with one or two partners for company. . . .
In the middle of St. James Town, along that ghost of Ontario Street, there are often impromptu markets
selling fruits and vegetables, while closer to Wellesley, by the Food Basics grocery store, a flea market runs
when the weather is good. One vendor who sells rugs along the Wellesley sidewalk can be seen, at the
prescribed time, kneeling in the direction of Mecca on those rugs. All this hits at the tremendous capacity
that is locked up in the surrounding towers. The people in them know how to make and do things and,
given the chance, could likely create a flourishing local economy.
. . . The city life is already here, it just needs some respect.
— Shawn Micallef, Stroll (2010, 15 and 288)
A second possibility has to do with the surrounding natural environment. Nature is
important to consider in this context because while “land” is more than “the physical
qualities of nature,” it still includes nature. Indeed, as Harvard economist Edward Glaeser
writes in The Triumph of the City, “Americans do seem to love warm weather. Over the
last century, no variable has been a better predictor of urban growth than temperate
winters” (2012, Kindle locations 1149–50). But not every city has nice weather and easy
access to abundant and beautiful natural amenities. What can these places do other than
throw up their hands in despair?
Jim Brainard, mayor of Carmel, Indiana, proposes a hypothesis: “We don’t have the
Pacific Ocean, we don’t have the Rocky Mountains. So we have to work harder on our
cultural amenities and in our built environment to make it beautiful—and to make it a
place where people want to choose, to spend their lives, raise their families, and retire”
(2009). That is, perhaps local authenticity can “compensate” when a place lacks those
natural endowments that “automatically” bless it with beauty and connect it to ample
recreational activities. Such communities may have added incentive to build a sense of
local authenticity and broadcast their charms more intensely to recruit and retain skilled
residents. If this is so, in places with fewer natural amenities, local authenticity could be a
bigger selling point, especially for highly educated persons looking to escape the
cosmopolitan rat race and settle down in a charming locale. That is, local authenticity
might substitute for nature in less naturally well-endowed settings.
So now we have three more propositions: (4) Bohemian neighborhoods should correlate
with population change and other indicators of economic growth when they are located
inside less Bohemian cities; in less traditionalistic surroundings the “Bohemian” dividend
should be weaker. (5) Local authenticity should be associated with growth in morewalkable places and (6) in places with fewer natural amenities.
Scenes Are Growth Factors
The performance score measures of scenes permit us to transform these ideas about scenes
as economic growth factors from interesting daydreams into empirically testable
propositions. To do so, we join our scenes variables with other variables, mostly from
census data. The general approach is the standard one in social science. One looks for
covariations and asks questions like, Where there are scenes that more strongly prize
personal self-expression, is there also population growth, job growth, income growth,
human capital growth, rental increases, greater innovation, and so on?
Of course, putting the question this way immediately raises the issue of spuriousness.
Perhaps the correlation we observe is not due to the scene but to some other factor. Maybe
self-expressive scenes are almost always located in high-population zones, and maybe
high-population zones have economic growth wherever they are, and without the fact that
they happen to be where numerous people are, self-expressive scenes would not be
connected with growth.
To guard against spuriousness of this sort, we include a battery of control variables in
our analyses. Which ones? The best candidates would permit us to rule out the possibility
that any correlations we observe between scenes and economic growth are due to some
other factor. The likeliest suspects are staples of the local development literature that have
been featured in past studies by experts on related issues: population, cost of living,
education, race, politics, and crime. We therefore control for these in all our US analyses,
and detail the similar variables for Canada, below. Chapter 8 describes variables and
methods of analysis in more detail.
In addition, we control for two other key variables. First is the local concentration of
cultural industry employment, to test whether any correlation between scenes and growth
is in fact due not so much to the overall aesthetic of the place but to the fact that this
specific group is present.8 Second, we also include as a control variable the most common
combination of scenes dimensions, which we featured in chapter 3—Gemeinschaft versus
Gesellschaft, Communitarianism versus Urbanity. Because this complex so sharply
defines the scenic differences across the country, we want to be sure that when we see a
connection, say, between self-expression and growth that this more specific observation is
not simply a function of the more general dynamic of Communitarianism versus Urbanity.
We call these eight variables the Core, which are listed in the note to figure 4.1. The
Core is included as independent variables in all our multivariate analyses in this chapter,
to provide a consistent benchmark for assessing results. We often add other variables,
however, in other chapters when these are relevant to the specific hypotheses we are
testing.
Figure 4.1
This figure shows how the impact of technology clusters on economic growth varies depending on the selfexpressiveness of the scene. It represents the interaction of self-expression and technology clusters. The graphics are
read left to right, where the x-axis indicates higher or lower self-expression performance scores (relative to the national
average), and the y-axis indicates the predicted change in six separate outcomes (again relative to the national average):
change in total jobs, change in income, change in total population, change in rent, change in the college graduate share
of the population, and change in the postgraduate share in the population. Change measures are from 1990 to 2000,
except for change in jobs, which is from 1994 to 2001 (due to data availability). Change in jobs, income, rent, and
population are measured as ratios (e.g., 2000 per capita income / 1990 per capita income); change in the college and
postgraduate shares of the population are measured as differences in proportions (e.g., 2000 college graduate percentage
of the population − 1990 college graduate percentage of the population). Predicted values are based on multilevel models
with counties as the level 2 units of analysis and zip codes as the level 1 units of analysis. Covariates include technology
industry concentration, (BIZZIP) self-expression performance score, their interaction term, and the Core (county
population, rent, party voting, and crime rate; zip code percentage college graduates; percentage nonwhite; cultural
employment concentration; and our factor score measure of Communitarianism/Urbanity). All variables have been
standardized to have mean equal 0 and standard deviation equal 1. Unless otherwise noted, all interactions are
statistically significant (p < 0.05). N is all US zip codes. More on variables and methods of analysis is in chapter 8 and
the online appendix (press.uchicago.edu/sites/scenescapes).
Any connection between a type of scene and economic growth we report is thus net of
the Core. That is, the below results show whether, regardless of education levels,
population levels, cost of living, and so on, zip codes with more self-expressiveness, or
local authenticity, or glamorousness, and so forth, have more economic growth.
How do we measure economic growth? The main dependent variables, or outcomes,
include the classics: growth in population, income, rents, and jobs. To these we add three
variables featured in recent literature on the postindustrial creative economy: patents, the
standard proxy for how innovative a local economy is; and gains in college graduates and
postgraduates, the typical measures of the human capital that leads to idea generation. All
nine outcomes are listed across the bottom of figure 4.3. Unless otherwise noted, the
changes we measure are from 1990 to 2000.
Besides the Core controls above, we considered dozens of others—from technology
industry clusters to January temperatures to county-wide attitudes toward women in the
workplace—to assess their impacts.9
Do Scene Differences Make a Difference?
Chapter 3 showed how our scenes measures identify strong differences in the cultural
character of places. That chapter ended with a challenge from William James: Do these
differences make a difference? Now we can be more specific: Are they merely spurious
icing or can they drive economic and social processes, as the discussion of the scene as a
factor of production suggests? Consider our hypotheses from above.
A Self-Expressive Scene Enhances the Impact of Technology Clusters on the Local
Economy
For this first proposition, about how self-expressive scenes provide fertile soil for
technology work, we turn to our US data. Our question is whether the impact of
technology clusters on various measures of economic development shifts as the scene in
which they are located becomes more or less self-expressive. Figure 4.1 shows that these
contextual dynamics do indeed often occur.
To read this type of figure, compare the x-axis, the y-axis, and the three lines. In figure
4.1, the x-axes show variation in self-expressive scenes: average self-expression is 0, and
then values along the axis are standard deviations above or below that average. The y-axes
are the economic development outcomes we are examining here: change in jobs, income,
population, rent, college graduates, and postgraduates. National averages are again scored
0, and units are standard deviations away from that value. Thus for job growth (as an
example), positive values indicate higher than average growth, and negative values
indicate lower than average growth. The three lines show average technology industry
concentration, high technology industry concentration (90th percentile), and low
technology industry concentration (10th percentile).
For the type of proposition investigated in figure 4.1, the key is to follow the three lines
while reading from left to right across a given x-axis. The patterns are striking. Start with
the upper left graphic, where change in total jobs is the outcome. At the far left, the three
lines barely differ: in less self-expressive scenes, high versus low technology industry
concentration makes little difference for job growth. As we follow the lines to the right,
they separate: in the country’s most self-expressive scenes, greater technology industry
concentrations are more strongly associated with faster job growth.
Box 4.13 The Multiplier Effect of the Innovation Sector
Innovative industries bring “good jobs” and high salaries to communities where they cluster, and their
impact on the local economy is much deeper than their direct effect. Attracting a scientist or a software
engineer to a city triggers a multiplier effect, increasing employment and salaries for those who provide
local services. In essence, from the point of view of a city, a high-tech job is more than a job. Indeed, my
research shows that for each new high-tech job in a city, five additional jobs are ultimately created outside
of the high-tech sector in that city, but in skilled occupations (lawyers, teachers, nurses) and in unskilled
ones (waiters, hairdressers, carpenters). For each software designer hired at Twitter in San Francisco, there
are five new job openings for baristas, personal trainers, doctors, and taxi drivers in the community. While
innovation will never be responsible for the majority of jobs in the United States, it has a disproportionate
effect on the economy of American communities. Most sectors have a multiplier effect, but the innovation
sector has the largest multiplier of all: about three times larger than that of manufacturing.
— Enrico Moretti, The New Geography of Jobs (2012, 13)
Self-expression also shifts the impacts of tech concentration on change in income, rent,
college graduates, and postgraduates. Look again at the far left side of the graphics for
each of these outcomes. The dotted lines (indicating high tech industry concentration) are
all lower than the dashed lines (indicating low tech industry concentration): in less selfexpressive scenes, growth in rent, income, college graduates, and postgraduates was
relatively weaker where tech concentrations were stronger. Then we follow the lines to the
right; they cross: in more self-expressive scenes, greater technology industry concentration
is associated with stronger growth in these outcomes. The impact of tech concentration on
population change, by contrast, does not seem to be affected by self-expression: the lines
stay close together all the way across, and do not separate to a statistically significant
degree.10 Still, on the whole, self-expressive scenes seem to be fertile economic soil
indeed.11
This idea of exploring how technology links with nontech factors extends cutting-edge
work in economic geography. UC Berkeley economist Enrico Moretti’s The New
Geography of Jobs, for instance, shows that innovation especially in the technology sector
drives the “new economy,” but also that technology clusters are the main source of more
and better jobs beyond that sector. A personal trainer in Silicon Valley is better off than
one living three hours away, in Visalia, he shows.
These results about how scenes heighten the connection between technology clusters
and economic development suggest that tech clusters on their own are not the whole story.
Rather, innovative industries come into their own and perform at higher levels when
coupled with the right scene: consumption does not only follow along in the wake of
production; consumption can enhance and improve production. While evidence for this
connection has typically come from anecdotes from the bars of Silicon Valley, San
Francisco, and New York, figure 4.1 shows that these are not unique cases but emblematic
of a broader and deeper connection.
Box 4.14
In a city like this the future jobs are going to come from the applied use of our collective intelligence. And
the way you encourage that is by fostering an atmosphere of creativity and allowing the entrepreneurial
spirit to succeed in that creative atmosphere. The creative economy has all sorts of aspects. So we’re here
in the Communist’s Daughter. This started around the same time I became mayor. And its success is
because of the same principles. People wanted a place where they could hear great jazz on a Saturday
afternoon and it’s funky and little and different. And it’s created jobs. These are creative jobs. The people
who work in here as servers and behind the bar are part of the creative economy. I think that side of what
the creative economy means isn’t well enough told. . . . It’s really about that spirit of innovation. . . . So,
when the City’s Agenda For Prosperity addresses creativity, I see it in all of those aspects . . . helping
newcomers succeed, supporting a vibrant arts and cultural scenes so for example workers who want to
work in the IT sector will live here because people who work in IT tend to be younger and like vibrant
cities that are fun and funky and interesting. And it’s about entrepreneurs like Paul who is the proprietor of
the Communist’s Daughter.
— David Miller (2011)
A Strong Renoir’s Loge Scene Enhances the Artistic Dividend
Our second proposition suggests that when artists are concentrated in welcoming scenes,
the artistic dividend increases. We test this hypothesis with our Canadian data, focusing on
a scene measure that approximates the scene embodied in Renoir’s Loge, which we
outlined in chapter 2. Combining glamour, charisma, self-expression, and formality, this
measure is based on a factor analysis of scenes dimensions constructed from Canadian
census of business data.12 It is strongly correlated with theaters and other items listed in
box 4.15 on key Renoir’s Loge amenities. And it is highly concentrated in Canada’s urban
centers, with all the 29 highest-scoring FSAs located in Toronto or Montreal (Toronto’s
highest-scoring FSA, M5V, contains the entertainment district; Montreal’s, H2W, is the
center of the Plateau Mont-Royal district and contains the highest percentage of artists of
any Canadian FSA).
We again examine changes in several indictors of overall local economic development,
in this case from 1996 to 2006: median family income, average employment income, and
so on. We also include in our analysis a battery of controls similar to the US Core group.
All variables are listed in the figure 4.2 note.13
Figure 4.2
This figure shows how the impact of the arts and culture share of the workforce on Canadian local economic
development varies across Renoir’s Loge scenes, measured as a factor score featuring glamour, charisma, selfexpression, formality, anti-utilitarianism, and anticorporateness (relative to the national average). It represents the
interaction of art and culture professionals with Renoir’s Loge. The graphics are read left to right, where the x-axis
indicates stronger or weaker Renoir’s Loge scenes, and the y-axis indicates the predicted change in six separate
outcomes (also relative to the national average): change in employment income, median family income, rent, population,
the university graduate share of the population, and the “creative class” share of the workforce. Change measures are
from 1996 to 2006. Changes in income, rent, and population are measured as ratios (e.g., 2006 employment income /
1996 employment income); changes in university graduates and the creative class are measured as differences in
proportions (e.g., 2006 university percentage of the population − 1996 college graduate percentage of the population).
Predicted values are based on multilevel models with census metropolitan areas (CMAs) as the level 2 units of analysis
and Forward Sortation Areas (FSAs) as the level 1 units of analysis. Covariates include the proportion of the workforce
employed as “professionals in art and culture,” Renoir’s Loge scenes, and their interaction, along with 1996 population,
rent, and university graduate and visible minority shares of the population, as well as 2000 Liberal Party vote share. All
variables have been standardized to have mean equal 0 and standard deviation equal 1. Unless otherwise noted, all
interactions are statistically significant (p < 0.05). N is all Canadian FSAs.
Figure 4.2 examines whether correlations between indicators of economic growth and
the share of the local workforce employed as professionals in arts and culture shift as the
scene more or less strongly approximates Renoir’s Loge. What do we find?
Box 4.15 Key (Canadian) Renoir’s Loge Amenities
This is an illustrative list of key amenities highly correlated with the Canadian Renoir’s Loge variable:
theaters, motion picture and video production, independent artists, writers, and performers, postproduction
and other video production services, agents and managers for artists and entertainers, motion picture
producers and studios, graphic design services, musical groups and artists, full service restaurants, sound
recording services, motion picture and video distribution, architectural services, cafes terraces,
photographic services, charitable and community organizations, restaurants, performing arts promoters,
social advocacy organizations, pastry shops, communication and public relations consultants, graphic
designers, marketing consultants, multimedia, periodical publishers, arts and cultural organizations
— The authors
The pattern in figure 4.2 is again striking. Start at the upper left, with changes in
employment income (i.e., wages) and median family income (a broader-based indicator of
income growth). Both show a similar pattern: arts and culture workers are in general
associated with income growth, but the association is strongest when artists live in a
Renoir’s Loge scene. On the far left end of the x-axes, the lines touch: in places with weak
Renoir’s Loge scenes, having high concentrations of arts and culture professionals does
not lead to much more income growth than having a low concentration. But follow the
lines to the right as they separate: where Renoir’s Loge is strong, a high arts and culture
share of the workforce meant faster income growth than in areas with relatively few
artists.
Change in rent shows a more dramatic shift across scenes, not only a change in degree
but a reversal. On the left side, the line for few arts and culture workers is on top: where
Renoir’s Loge was weak, rents increased more where there were few artists compared to
where there were many. However, follow the lines to the right into areas with stronger
Renoir’s Loge scenes; they cross. Here, places with strong artist concentrations had bigger
increases in rent than places with low concentrations. Change in population has a
somewhat similar pattern: where Renoir’s Loge was weak, population growth was much
higher in places with few artists. As we move to the right, however, where population
growth in general was slower, the lines come together, and artist concentrations are not a
(relative) drag on growth.
Now look at changes in university graduates and the creative class. The impact of artist
concentrations on university graduates is similar to their impact on income: it steadily
increases as the scene becomes stronger. The effect of artists on creative-class growth,
however, reverses as the scene changes. In less glamorous, charismatic, and selfexpressive scenes, artist clusters had relatively low growth in the creative class; when
joined with a scene that supports self-expression, glamour, and charisma, artists attracted
the creative class. The creative class, in other words, does not seem to be as strongly
drawn to artist communities without the right amenities. Instead, they grow where artists
and amenities join to make a more compelling overall scene.
Overall, in line with the ideas of Richard Florida and Ann Markusen, we thus find
strong links between artists and overall economic development. But these connections are
often strongest when artists live amid the Renoir’s Loge combination of glamour,
charisma, and self-expression. Outside of this context, relationships between artists and
economic growth are often weaker. These results suggest that the artistic dividend does
seem to be enhanced when artists are surrounded by a supportive scene.
Self-Expression and Glamour: Two Core Drivers of General Economic Growth
These are strong indications that especially those scenes that prize glamour and selfexpression provide noneconomic bases for economic success. We would therefore expect
to find that they are linked not only with rising rent but all manner of economic
development. And that is what we do find, at least in the United States, as in figure 4.3.
Figure 4.3
This figure shows the impacts of three (BIZZIP) performance scores—self-expression, glamour, and tradition—on nine
economic development outcomes (listed across the bottom). It summarizes three separate analyses. In each, the full
model includes the Core (see note to figure 4.1) plus one of the performance scores. Black circles indicate statistically
significant (p < 0.05) positive associations, hollow circles indicate statistically significant negative associations, and
blanks indicate that there is no statistically significant association. Circle sizes are proportional to the magnitudes of
coefficients from multilevel models, where counties are the level 2 units of analysis and zip codes are level 1. All
variables have been standardized to have mean equal 0 and standard deviation equal 1. Because patents are county-level
variables, they are analyzed with ordinary least squares (OLS) models, and circle sizes are proportional to standardized
coefficients. N is all US zip codes.
To read this type of figure, the key is to look at the black and white shading and sizes of
the circles. A bigger circle means a stronger relationship (e.g., between self-expression
and change in jobs). A black circle indicates a positive relationship (more self-expressive
scenes, greater job growth); a hollow circle indicates a negative relationship (figure 4.3
has no hollow circles, but figures in later chapters do). If a circle is present, the
relationship is statistically significant (i.e., not random), even adjusting for the controls we
discussed above (the Core). If there is no circle, the relationship is not statistically
significant, as is the case for traditional scenes and all outcomes.
Box 4.16 Creatives Grow Better in the South West (2008) (excerpt from a
satirical video)
Filmed on location at the Wedmore Creative and Artist Farm, Somerset, England, in 2008. Pan in on an
idyllic farm setting. An old farmer walks through a rolling field, which is filled with young, ripe “creatives”
sprouting from the soil.
Yeah, I reckon we been in this business about three centuries this family. We do about 250 a year,
something like that. (Walks up to a young man in full hipster gear.) Well, he looks nice and ripe, doesn’t he.
Yeah, bein’ creative people it’s important they get a lot of praise, you know, massage their egos, especially
just before the harvest . . . (Approaches an older man.) Oh, look here, now he missed his harvest. He’s
useless, he’s no good to anyone. So we just leave him there as a reminder. (Enters the farmhouse. Creatives
are being crushed in a large juicer.) This is the hydraulic juicer. Now we used to wind these down by hand
in the old days. But these modern ones, they’re great, they give you 10% more juice per pressing. Thirty
tons per square inch comes through that ram there, squashes them flat. Juices run out, down there, through
that funnel, into that tank. And . . . here we are, pure creative juice, that is. No, don’t bloody drink it!
Christ, It’ll blow your bloody head off, that would . . . (Moves to a loading area.) Well this here is the
distribution center where we get all the juices ready to send out to all the people in the South West, all the
companies, that need creativity. We’ve got Bristol Blue, that’s good for online and direct marketing
campaigns. Right here we’ve got the Plymouth Peculiar, that’s used mainly for TV ads and the like.
What stands out is how broad and deep the link is between self-expression, glamour,
and growth. Rent climbs at relatively high rates in places with scenes strong in both
dimensions. But not just rent. Glamour and self-expression are significant drivers of seven
of our nine outcomes (listed at the base of figure 4.3)—of the more than 20 variables we
examined, they had the broadest positive impacts on numerous economic growth
indicators. Glamour and self-expression were in fact more consistently important than
such urban development staples as growth and level of human capital, arts jobs,
technology jobs, population density, and commute times.
And glamour and self-expression were not only broadly linked with key outcomes; they
were sometimes strongly linked. For instance, no other variable in our Core group shows
as strong a link with population growth as does self-expression. And only the median
county rent and the concentration of artists are more strongly linked with college graduate
gains than are glamour and self-expression. In other words, if you wanted to predict which
places would enjoy the most robust economic development through the 1990s,14 not only
college graduates or tech but the degree to which the local scene prizes an improvisational
attitude toward life and a glamorous way of displaying the self is one of your best bets.
Traditional scenes, by contrast, were not linked with economic outcomes either way,
positive or negative. It would be a mistake, however, to conclude that the more
communitarian dimensions of local scenes have no role to play in economic development,
and that young, flexible creatives are the only game in town. College graduates and some
other economic growth indicators are rising where the scene evinces more local
authenticity; rent is rising in more neighborly scenes. And both neighborliness and local
authenticity are linked with patents (not shown).
This last finding about patents goes so much against the grain of much of the urban
development literature that tends to focus on the more urbane and experimentalist
dimensions of innovation that we did not believe it ourselves at first, and ran many tests to
verify whether it was just statistical noise. It does not seem to be. Rather, our conclusion is
that most analysts miss the connection because neighborly scenes, local scenes, and
patents all tend to be in high rent districts (like Silicon Valley), and they mistake rent for
the main event. But once one controls for rent, the link between neighborliness and patents
is robust.
Innovation, that is to say, has many dimensions other than rule breaking or show
stopping. It is often emotionally taxing, marked more by failure than by success. Being
rooted in a warm, stable, supportive, and trusting environment could encourage
perseverance through difficulties. And some of the best new knowledge can be like the
best food: it comes slow, not fast, organically connected with local practice, rooted in the
particular dynamics of a concrete place and community.
Box 4.17 Well-Appointed Guest Rooms, and Tattoo Suite Down the Hall
The sun had long since set when the design—an intricate garland of roses and a few skulls drawn on the
skin in Sharpie marker—finally dried and it was time to begin tattooing the client, who had arrived shortly
before 4 p.m. The usual accoutrements—individually wrapped needles and tubes, containers of ink and
antiseptic, and a smear of A+D ointment—were fanned out across a table next to the artist.
“He’s going to start on the most painful spot,” the client, Rich Hilfiger, said with a smile as the tattooist
held the gun aloft, staring intently and grasping an ounce of flesh between the shoulder and collarbone.
“I’m feeling really good about this,” Mr. Hilfiger’s girlfriend, Krystal Martos, chimed in, despite
protesting earlier that watching the process would almost hurt her more than him.
It was a scene that unfolds along low-rent commercial strips in towns big and small, but this was no
storefront tattoo parlor, with neon signs in the windows and folding chairs in cramped quarters. Instead, it
was the pop-up studio of Mister Cartoon—a tattooist who counts Eminem, Beyoncé and Mena Suvari as
clients—at the Marcel at Gramercy, an upscale boutique hotel looking to distinguish itself from the pack.
As part of the hotel’s artist-in-residence series, Mister Cartoon, who is based in Los Angeles and usually
has a three-to-six-month waiting list for appointments, which can cost tens of thousands of dollars, has
created original artwork that hangs in the lobby. And from Nov. 14 through Wednesday, he is offering his
services out of a two-bedroom suite. . . .
A veteran graffiti and airbrush artist and an illustrator for magazines and album covers, Mister Cartoon,
whose given name is Mark Machado, began tattooing in the mid-1990s, but things did not really take off
until a prominent tattooist promised to mentor him 13 years ago if he stopped drinking and smoking. He
did, he said, a move that has helped him build a business that now includes a marketing agency and
partnerships with several apparel companies.
“I’m a whole different person,” he said, adding that he was now a homeowner and married with four
children.
— Diane Cardwell (2010)
Bohemian Islands in Communitarian Seas Lead to Growth, but Not Elsewhere
And what about Bohemia? The suggestion above was that the allure of Bohemia should be
linked to the character of its surroundings. To test this idea, we construct a bliss point
measure, based on the scene profile of all US zip codes against the ideal-typical Bohemian
profile from chapter 2. Zip codes closer to that ideal type are defined in this way as more
Bohemian. This measure of Bohemia is strongest in high crime areas where many artists
live but relatively few college graduates, tech workers, or R&D workers are nearby.
Moreover, it tends to be in places where, according to the DDB lifestyle survey, the typical
person, when asked whether he considers himself to “be a hard worker,” is somewhat
likely to say “no”—that is, where the bourgeois, nose-to-the-grindstone work ethic, is
relatively weak.15
Our analysis examines how the impact of a variable (in this case Bohemia) on
indicators of economic growth varies across contexts. The context here is the county
average score on our first US scenes factor, Communitarianism/Urbanity. This gives a
measure of the general county scene, running from more communitarian counties (on the
left end of the x-axis), which are more traditional, neighborly, and formal, up to less
communitarian counties (on the right end of the x-axis), which are more rational,
corporate, utilitarian, transgressive, and glamorous. The idea, again, is to examine whether
the economic impacts of Bohemia shift as their surrounding scenes become more or less
communitarian.
Figure 4.4 suggests that the economic impacts of Bohemian zip codes are in some cases
stronger when they contrast their surroundings, that is, when located in a more
communitarian surrounding county. More Bohemian amenities predict increases in income
and population when in more communitarian counties; as the county becomes less
communitarian and more urbane, more versus less Bohemianism makes a smaller
difference for income and population growth—in fact, for income growth, the relationship
reverses in the least communitarian counties (at the far right), and less Bohemian zip
codes had higher income growth than more Bohemian ones. Similarly, in the less
communitarian (more urbane) counties, more Bohemian places had fewer high-tech and
entertainment patents than less Bohemian places, and in the case of entertainment patents
the relationship reverses in more communitarian counties. Yet the positive relationship
between Bohemias and job growth does not shift across county Communitarianism: the
distances between the three lines do not change in a statistically significant way as they
move across the x-axis.16
Figure 4.4
This figure shows how the impact of Bohemia on economic development varies depending on how communitarian or
urbane the surrounding scene is. It represents the interaction of the (zip code) Bohemia bliss point with county average
Urbanity. The graphics are read left to right, where the x-axis indicates Communitarinism/Urbanity, and the y-axis
indicates the predicted change in six separate outcomes: entertainment patents, high-tech patents, change in population,
change in income, change in total jobs, and change in the postgraduate share of the population. Except for the patents,
predicted values are based on multilevel models with counties as the level 2 units of analysis and zip codes as the level 1
units of analysis. Because patents are county-level variables, they are analyzed in ordinary least squares (OLS) models.
Covariates include the Core (see note to figure 4.1). To the Core, we add our (BIZZIP) bliss point measure of Bohemia
(defined in the online appendix), the county average Urbanity, and their interaction term. We measure
Communitarianism/Urbanity with a factor score that combines multiple scenes dimensions: higher Urbanity means more
glamour, transgression, corporateness, rationalism, and utilitarianism; lower Urbanity means more neighborliness,
tradition, and formality. All variables have been standardized to have mean equal 0 and standard deviation equal 1.
Unless otherwise noted, all interactions are statistically significant (p < 0.05). N is all US zip codes.
These figure 4.4 results provide qualified support for our proposition about Bohemian
islands within communitarian seas being conducive to growth.17 More generally it
underscores the importance of considering contextual scene characteristics, which qualify
the common reasoning that “to be creative, we need more Bohemian folks.” These scene
results suggest that, on the contrary, Bohemias can add value (as measured in economic
development terms) if they are surrounded by more communal, even anti-Bohemian
people and institutions.
Conversely, if an area already has a generally less traditionalist ethos, adding more
Bohemian people or facilities or programs (if we are pondering local policy options) may
have small economic impact. When Bohemia is not anymore an island in a communitarian
sea, that is, but just one style in a more diverse (urbane) context, the intensity of its
countercultural resistance to its surroundings is weaker, and its economic effects less
distinct. The contrast between establishment and radical is reduced, and specifically,
Bohemian neighborhoods stand out less both as innovation centers and talent attractors.
One indication of this moderating of Bohemia in less communitarian contexts is that
postgraduate degree holders—harbingers of the establishment18—actually increase in
Bohemias located within the least communitarian parts of the country, as figure 4.4 also
shows.19
Local Authenticity Can Sometimes Be Enhanced by Walking and Compensate for a
Lack of Natural Amenities
Finally, let us test the ideas about local authenticity: that the charm of the local scene can
be heightened by routinely walking through it and might compensate for a lack of natural
amenities. To do so, we look (in figure 4.5) at how the impacts of local authenticity may
vary across contexts of walkability and access to natural amenities.20
Figure 4.5
This figure shows how the impact of (BIZZIP) local authenticity on population and postgraduate growth varies across
walkable and natural amenity contexts. It represents (on the left) the interaction of local authenticity and walkability and
(on the right) the interaction of local authenticity and natural amenities. The graphics are read left to right, where the xaxis indicates walkability (on the left) and natural amenities (on the right), and the y-axis indicates the predicted change
in two outcomes: change in population and change in the postgraduate share of the population. Predicted values are
based on multilevel models with counties as the level 2 units of analysis and zip codes as the level 1 units of analysis.
Covariates include the Core (see note to figure 4.1). To these we add for the left graphic local authenticity, walkability,
and their interaction term; for the right, local authenticity, natural amenities, and their interaction term. All variables
have been standardized to have mean equal 0 and standard deviation equal 1. Unless otherwise noted, all interactions are
statistically significant (p < 0.05). N is all US zip codes.
Figure 4.5 suggests that for some outcomes the context makes a difference for the
growth potential associated with local authenticity. Look first at the left graphic. As we
follow the lines of local authenticity to the right, walkability increases, and the lines cross
and spread out: where more people walk to work, the impact of local authenticity on
population growth is strongest. This result gives some qualified support to the proposition
that when people slow down to engage with a strong local culture, that culture may
become more attractive, a simple idea illustrating potential scene-specific impacts on
growth.
Box 4.18
There was as much freedom [in Greenwich Village] as before, but since it was equaled or even surpassed
[in the suburbs], where was the defiance and the revolt against convention which once infused Bohemia.
— Milton Klonsky, “Greenwich Village” (1948, 458–59, 461)
Now look at the right graphic. If we follow the lines from right to left, we move from
places with more to less natural amenities. As we do so, we see that places with few
natural amenities and higher local authenticity are associated with relative increases in the
postgraduate share of the population.21 This pattern seems to resonate with Mayor
Brainard’s intuition. While natural amenities certainly can be key factors in driving
growth, other amenities (often constructed, like festivals or gardens or B&Bs or libraries)
can, at least for some persons (e.g., postgraduates), compensate for having low or average
access to natural amenities. This is a far more encouraging result about the potential of
local policy makers to build an attractive scene than what many accounts offer, which
often imply nothing can be done. Richard Longworth’s (2008) account of Midwest cities
and towns, Caught in the Middle, for instance, shows that a few places like Chicago and
Kalamazoo have made strides toward creating new scenes to adapt to the decline of the
rustbelt manufacturing economy, but many other locations are just quietly declining.
It is not easy to create attractive local authenticity, but these results are more sanguine
than Longworth’s picture. There are many examples of success as well as failure. Still, our
analysis provides an intriguing glimpse at this counterintuitive Brainard effect, while
showing that Brainard may speak for many others, who, by being sensitive to their local
context, can make a real difference. “If you have lemons, make lemonade”—a policy
motto to which we return in chapter 7, which reflects on general implications of scenes for
local policy.
Conclusion—“Every Man a Musician”: Throwing Open the Garret Gates
The general message of these results comes out loud and clear: The cultural character of a
place is a strong determinant of its economic fortunes.
We conclude this discussion of economic impacts of scenes by reflecting on what the
results imply on a broader level, returning to the higher plane of the discussion of land,
labor, and capital. Max Weber again provides a useful point of departure. He was fond of
using the phrase “every man a monk” to characterize the world-historical—especially
economic—implications of the Protestant Reformation.
By this, he meant that the Reformation threw open the walls of the monastery, injected
its ascetic element into everyday life, and offered positive religious backing for the
focused, disciplined, and rational exercise of mundane activities like work and household
management. Normative ideals formerly restricted to religious virtuosi were extended to a
wider population, tremendously expanding and deepening the personal religious
commitments and experiences available to them. Heightened expectations of disciplined
performance as an everyday occurrence, outside of specialized settings, generated new
anxieties and conflicts.
And, most fatefully, the productivity gains that followed created what philosopher
Charles Taylor calls a “disciplinary revolution” (Taylor 2007, ch. 12). The rest of the
world became encased in the “steel shell” of capitalism, as Weber famously described it. If
Calvinists pursued work with the ascetic zeal of a religious calling, others for whom
worldly toil was a burden were thereby forced to work harder or move aside.
Things have changed since Weber’s times. Not “every man a monk” but “every man a
musician” could describe the situation in general, if not perfectly accurate, terms. The
walls of the lab, lecture hall, and Latin Quarter have been thrown open, injecting
expressive and creative elements into everyday life. Practices and sensibilities formerly
restricted to creative virtuosi have been extended from the garret, studio, and study to
boardrooms, city halls, office cubicles, and main streets.
This marks a great upgrading of the expressive and creative possibilities available to the
general populace. It also subjects more individuals to previously more exclusive anxieties
oriented around the quest for authenticity and the demand to construct meaning for
oneself. And as politics has grown ever more populist, ratcheted up still further after 1968,
the literal meaning of “everyman” has shifted from the politically active of past centuries
to include more men and women than ever. This is clearest in the Western democracies, of
course, and large parts of the world remain important exceptions.
We are witnessing in many geographic areas the institutionalization and internalization
of creativity. Like the Protestant ethic, it has transformed the economic playing field.
Places that best facilitate idea and style generation are succeeding, even if success is not
due to any single factor, whether it is education, basic research, technology, artists,
tolerance, or the scene. In any case, this is a world that Weber would have hardly
recognized.
Has it thrown up an iron cage of creativity? Innovate or die? Bohemia or bust? There is
no one, clear answer in these analyses. We do find that many places encouraging residents
to express and glamorously display themselves are at the leading edge of the creative
economy, yet they do not have a monopoly on innovation or growth. Other places with
neighborly scenes also grow and innovate. Some places that root residents in the local or
keep them in contact with nature are growing, innovating, and attracting people with
education and skills. Nashville’s country music industry rivals music industries in New
York and Los Angeles. Yet each city’s musical genres feed on the strikingly different
amenities and scenes: three of the five most abundant types of amenities in Los Angeles
are jewelers, bakeries, and commercial artists; in New York the top categories include
jewelers, delicatessens, and art dealers. The most numerous amenities in Nashville are
automobile customizing services, Methodist churches, and the Church of Christ.
These distinctive patterns tell a powerful story about local cultural soils fostering
different scenes with different economic consequences, a quite different story than one
which omits land. Of course, scenes have other consequences beyond economic growth.
They are not only land for working; they are also habitats for living. Chapter 5 thus turns
to the links between scenes and the composition of residential communities.
5
Home, Home on the Scene
How Scenes Shape Residential Patterns
As you enter the Chicago Bronzeville neighborhood on the grand boulevard of Martin
Luther King Drive, you are welcomed by the bigger-than-life statue of Soulman. Soulman
is a young black man with his head high, sporting a large-brimmed hat and a suitcase tied
closed with rope. His entire body seems covered with fish scales, but look more closely
and they are the soles of shoes. They remind us of the many shoes worn out walking the
Underground Railroad from the Deep South to Bronzeville. Soulman was a brave pioneer
who escaped his slave master for the promise of freedom. The number of Soulmen
courageous enough to risk the Underground Railroad was tiny, but they inspired thousands
who followed in later years.
Figure 5.1
Soulman in Bronzeville, Chicago
The symbolic heritage of Soulman remains strong in contemporary Bronzeville. Its
thousands of new mixed-income housing units are surrounded by numerous churches,
large and small, and strong memories of blues and gospel, which were pioneered here.
Richard Wright read his works at the Wabash YMCA. He is one of dozens commemorated
in the bronze plaques lining the sidewalks of King Drive. These scenes that grew up
around Bronzeville’s historic legacy played a role at the turn of the twenty-first century, as
Mary Pattillo (2008) documents in Black on the Block, in attracting many new middleincome residents who could have chosen to live elsewhere. They found a rich symbolic
repository of historically potent images and aspirations, where song, sermon, solo, dance,
verse, and more provide venues for critical judgment of, respite from, and creative
engagement with an often harsh and hostile world.
Bronzeville of course embodies just one type of scene. The ghosts of Allen Ginsberg
and Jack Kerouac still haunt Greenwich Village and Haight-Ashbury, and scenes that
evoke Bohemian and Beat themes of self-expression and transgression are significant
draws for young people and artists to this day. Similarly, pastoral images of the
countryside, with its slow rhythms and quiet communities, often speak to older persons.
Many spend their golden years of retirement “on the road,” in RVs rolling through
America’s great scenes of natural beauty. Other retirees, particularly “ruppies” (retired
urban professionals), may be drawn to emerging downtown scenes, with amenities like
restaurants, operas, symphony halls, and parks.
Different people are drawn to different scenes. The character of the scene plays a major
role in determining who lives where and therefore what shape residential communities
take. To be sure, more than amenities define the opportunities and attractions that places
afford to current and potential residents. Hence it is crucial to analyze multiple variables
and multiple units of analysis.
Simple as this idea is, the major traditions of urban analysis have tended to propose
one-factor, one-level explanations, with jobs typically taking center stage. There is a
certain plausibility to this approach. Counties (or metros) generally constitute single labor
markets. If finding a job is the major motivation for moving, then any neighborhood
within a given labor market is, all things considered, as good as any other—jobs anywhere
in the city draw people from many neighborhoods and backgrounds, according to this
tradition. Hence many quantitative studies typically report large area data on economic
and population change for entire counties or metro areas. Ethnographers by contrast often
conduct case studies of individual neighborhoods, which generally ignore national or
global patterns. And national surveys of individuals largely omit their neighborhoods.
However, if we admit that choosing a place to live involves a more wide-ranging and
complex set of considerations, the analytical picture changes. In particular, residents of
different neighborhoods have ready access to widely varying amenities and scenes, even
within the same city. Chicago is a case in point. Just north of Bronzeville is the four-mile
area around the Loop, which attracted in the 1990s more 25- to 34-year-olds and college
graduates, relative to the metro area, than any other downtown in the entire United States.1
Many attribute the popularity to the four months of free or inexpensive concerts and
related Loop restaurants and nightlife. Rents escalated as these young urban professionals
moved in. Yet in other Chicago neighborhoods, population and rent were stable, while still
others have been seriously declining, such as those near abandoned steel factories. Data
for the whole county sums these many neighborhood-specific dynamics, which are lost
when aggregated.
Chicago is similar to most big cities in illustrating such neighborhood-specific diversity.
To capture such diversity analytically requires a more wide-ranging approach. We need to
compare local communities to one another, both within and across the cities in which they
are situated. And we need to incorporate jobs and income measures along with newer
dimensions like glamour and self-expression and newer amenities (at least in America)
like yoga and martial arts clubs. The point in doing so is not to disagree with past results
so much as to show how they can be enhanced by adding scenes concepts and measures to
the story. What emerges is a novel picture of why people live where they do and how
residential patterns are changing.
Chapter overview. A few main types of questions guide the following analyses. A first
question asks which types of scenes attract which types of people. We find links between
scenes and population changes across many subgroups: young people tend to increase in
transgressive scenes, baby boomers are rising where self-expression and local authenticity
mix, and retirees are increasing both near natural amenities and in places rich in the arts.
Moreover, Bronzeville is not alone in having a scene linked with African Americans:
historically concentrated in more communitarian scenes, African Americans have been
shifting somewhat away from such scenes and toward those that mix glamour and
exhibitionism. Scenes matter not only to the young, educated, and the affluent, but also to
middle-aged, older, and nonwhite persons.
We also ask how scenes distinguish within and transcend powerful social cleavages,
like race, religion, and education. Contra the idea that artists constitute a distinct new class
or homogeneous consumption group, we find that arts jobs are found in several different
scenes. Similarly, we question the extent to which America is “coming apart” along a
great cultural divide. There are to be sure major cultural differences across neighborhoods:
the proportion of college-educated whites is relatively large in zip codes with yoga studios
but small in those with evangelical churches; vice versa for nonwhites. However, some
amenities bridge these differences. Popular culture (e.g., fast food, pop music, and sports)
is an American lingua franca, well represented across communities with very different
ethnic compositions but also in more highly educated zip codes. So are martial arts clubs,
which are found near yoga studios and evangelical churches, in racially diverse and highly
educated neighborhoods—openness to alternative traditions and cultures is not distinctive
to any one group of Americans. What emerges is a far more crosscutting and pluralistic
picture of American life than many popular accounts offer, which stress black-and-white
fragmentation without showing potential commonalities and opportunities for meeting
“the other” in shared pursuits and activities.
We pursue these questions and more below. But throughout, the general importance of
the scene to urban development comes through loud and clear. Cities grow and change not
only because they have beaches or jobs, but also because they offer distinct scenes that
attract different types of people.
The New Chicago School
The Bronzeville example illustrates why it was no accident that what became known as
the Chicago School of urban sociology emerged in the city of Chicago, with its distinctive
focus on the neighborhood and the local context.2 Because of our own focus on local
context, we have often described our scenes approach as part of a New Chicago School.3
Highlighting the local scene extends the classic Chicago School focus on shifts in lifestyle
across neighborhoods. Yet it abandons the Old Chicago School nostalgia for village life
and rigidity about where different types of neighborhoods should be located (e.g., in
concentric circles). At the same time, the New Chicago School approach adds a much
more pluralistic, crosscutting, wide-ranging, and flexible sensitivity to the cultural themes
that can differentiate and link neighborhoods. To better understand how a scenes-based
New Chicago School extends and diversifies the ethnic neighborhood-based Old Chicago
School, it helps to first go back to the classic idea of studying the local context and then
see why it is important to expand our vision from the neighborhood to the scene.
The Types of Glue That Hold a Community Together Shift by Local Context
While Marxian analyses of urban change tend to downplay local context and stress
abstract forces like industrialism or capitalism, these seemingly universal processes have
their own local roots. Indeed, in some of the classic eighteenth-century English factory
towns, manufacturing workers from many backgrounds were thrust together in new types
of neighborhoods built around a factory. All of a sudden, their residences and daily
contacts were determined primarily by proximity to their place of work and their role in
that workplace. They came from far and wide to live near where the jobs were, and this—
the job—was the common thread in their residential life, more than, or at least alongside,
their homeland, language, or ethnicity.
In extreme cases like Pullman Town (outside Chicago) or Saltaire (near Bradford,
England), whole towns were planned and built around the company, and workers were
expected to rearrange their lives according to the fact that they were Pullman or Saltaire
workers. In Saltaire, not the cathedral but the textile mill was at the center of the village.
One worker described life as a Pullman employee as follows: “We are born in a Pullman
house, fed from the Pullman shops, taught in the Pullman school, catechized in the
Pullman Church, and when we die we shall go to the Pullman Hell” (“Quote from a
Pullman Laborer, 1883”).
Similar plans were developed elsewhere. George Steinmetz (1993) has shown how in
late nineteenth-century Germany paternalism and ideology led the Social Democratic
Party, corporate leaders, and local officials to agree to build housing for workers next to
their factories. This model spread with socialism to Soviet areas and China.
But not everywhere. The link between work and residence is relative to the local
context. Had Marx visited early twentieth-century Chicago, he would have seen this type
of contextual relativism on the ground. Here, distinctive ethnic groups—Irish, Polish,
Lithuanian, Italian, and so forth—lived not near factories but instead built and lived near
their own parishes; they often worked far away from their homes. Without the national
state as a focus of ethnic identity, as in European nations, the neighborhood became
central. Though Chicago is more extreme, America is dotted with Greektowns, Little
Italys, Chinatowns, Little Portugals, and the like.
Box 5.1 The Chicago Saloon
Irish Catholic dominance of the political and governmental systems of the city is a fact of life in present
day Chicago and has been so for many years. The first two major ethnic groups who came into the city
from Europe were the Irish and the Germans. While the Germans were an important segment of the city’s
body politics, the Irish had several advantages which they parlayed into a dominant political role. They
spoke and understood English. They were familiar with the English local political and governmental
institutions on which the American system was based. They were neutral outsiders in the traditional ethnic
antipathies and hostilities which the Central and East European ethnic groups brought to America from
their homelands. (“A Lithuanian won’t vote for a Pole, and a Pole won’t vote for a Lithuanian,” according
to a Chicago politician. “A German won’t vote for either of them—but all three will vote for a ‘Turkey,’ an
Irishman.”) And, finally, the Irish became the saloonkeepers in cities like Chicago, and the Irish-owned and
-run saloons became the centers of the social and political activity not only for the Irish but also for the
Polish, Lithuanian, Bohemian, and Italian immigrants who poured into the city after the Irish and Germans.
For where would an ethnic laborer go for recreation at night after his twelve-hour stint in the steel mills or
the stockyards but to the local saloon?
— Milton Rakove, Don’t Make No Waves, Don’t Back No Losers (1975, 33)
This residential pattern—the ethnic neighborhood—reinforced ethnocultural styles
through parades and food and bars and more. Saloons, church halls, and ethnic militias
became the centers of social and political life, not only union halls and revolutionary
cafes. Indeed, if we look to our amenities data, we find that to this day there is a strong
correlation between the number of Italians who live in a given neighborhood and the
number of Italian restaurants in that neighborhood, far stronger than for people of German,
French, and Irish ancestry and “their” restaurants. Some new immigrants like Koreans or
Jamaicans create new churches and restaurants in the same general manner.4 Even when
people move away from the ethnic village, the density of shops, restaurants, churches,
festivals, and the like in the old neighborhood provides a symbolic focus and a point of
congregation at night and on weekends.
At the same time, when this spatial concentration of ethnic culture seems to be on the
way to dilution, it can inspire feelings of anxiety and loss. Hence the Los Angeles School
of Urbanism, with its claims about the fragmentary, conflictual, Nowheresville character
of modern urban life, has its roots in its own distinctive neighborhood experiences: the
Los Angeles of disconnected neighborhoods, large single-family homes in gated
communities on sidewalk-free streets, freeway commutes, globetrotting stars, gangs,
violence, and international media corporations. Even generalized claims about the
schizoid character of modern life have their local bases.5
Where ethnic neighborhoods have been strong, religion, heritage, and culture have often
provided more important bases of allegiance and enmity than has class. This is a legacy
we saw clearly in chapter 3, documented in the number of family restaurants, parks,
cemeteries, and churches in Chicago. Indeed, it is this strong linkage between residence
and ethnic culture that is a central part of the answer to Werner Sombart’s classic question:
Why is there no socialism in America? The (partial) answer is that in contexts like the
United States in general and Chicago in particular, ethnicity and religion are often more
important for politics than is class. But different contexts generate different answers, a
theme to which we return in chapter 6.
The strong linkages in Chicago between neighborhood, ethnicity, religion, and culture
made the typical Chicagoan into something of a cultural anthropologist. Different people
have their own ways of life, their own ways of making sense of the world, which are
manifested in their daily rituals, how far they stand apart, dinner table manners, home
décor, leisure pursuits, and more. Chicagoans did not need to travel to the Amazon to learn
this; they just walked across the park.
Marx’s intellectual disposition was to extrapolate what he saw in specific local contexts
to impending global and epochal changes. Old ways of living together would be swept
into the dustbin of history by the coming proletarian tide. The Chicago approach is more
pluralistic and pragmatist: the strength of different types of social bonds varies in different
local situations. In places where work and factories are the focus of life, jobs and class
take center stage; elsewhere, other things matter more.
Box 5.2 An Old Chicago Joke
A man from China immigrated to Chicago. He opened up a laundry business in West Town, and worked
day and night for decades without so much as taking a single day off. He prided himself on his English,
conversing daily with his many customers. Finally, after over twenty years, he decided he had earned a
break. So he took a trip downtown, to the Loop, to see the sights. To his amazement, nobody understood a
word he was saying! He was beside himself. Had he suddenly forgotten everything he had learned in these
twenty years? A friendly face pulled him aside, and whispered in his ear: “You want to know why nobody
understands you?” He nodded. “You’re speaking Polish.”
— The authors
There Goes the Neighborhood
Scenes analysis extends this contextually sensitive neighborhood focus into a world in
which not only the church and local pub but also the nightclub, the farmers’ market, the
dance club, the yoga studio, and the dojo define the distinctive character of a place. This is
similar to going “back to the land” as in chapter 4, while adding new and more wideranging cultural dimensions that affect people in more than their jobs. In chapter 4 this
meant taking a more expansive view of how the character of a place influences economic
growth, not only attending to physical soil or even Max Weber’s Puritan ethic. So too in
this chapter: to go “back to the neighborhood,” we need a broader view of what
“neighborhood culture” means to understand the energies that can make a place attractive
for habitation and not only production. Hence extending the Old Chicago School
neighborhood context means moving on to the New Chicago School scene.
This extension of “neighborhood” to “scene” is not an abstract claim. It has grown out
of concrete local experiences, which the streets of Chicago made particularly evident. For
if “you deliver your precinct, I’ll deliver mine” was the political result of Chicago’s
everyday contextual relativism, it also made Chicagoans highly sensitive to new styles of
life, new forms of group togetherness, making their way into their bars and restaurants.
Thus it was in Chicago that a group label was forcefully applied to a new social type: the
yuppie.
Given the strength of local cultural identity in Chicago, it was immediately apparent in
the early 1970s that there were new characters on the scene. They stood out, for
Chicagoans were always sensitive to “outsiders” in their midst. These newcomers were
more likely to drink wine than beer. They engaged in strange new practices, like jogging
or jazzercise. They were just as likely to be found in the yoga studio or meditation center
as in the church. And so Chicagoans identified them by name—young urban
professionals, yuppies—and treated them like any other ethnic group. They have their
bars, and we have ours; they should live in their neighborhoods, and stay out of ours; and
so on.6
Box 5.3 Apocalypse Now
“If the future is the apocalypse,” Bridgeport native and artist Ed Marszewski declaimed to the New York
Times in February, “then Bridgeport is the community of the future.” Marszewski should know: as the
leader of Lumpen, an artist collective headquartered in Bridgeport, and the editor of that organization’s
eponymous periodical, Marszewski is used to making such statements in order to draw attention to a host of
social and artistic causes he finds firsthand in the neighborhood’s warehouse shadows. History would seem
to justify Marszewski’s macabre gesture. Bridgeport is arguably the most “Chicagoan” of Chicago
communities; marked by a history of violent racism, class conflict and corrupt machine politics, the
neighborhood includes the now-empty shells of stockyards and killing floors that made Chicago the “hog
butcher to the world,” as well as the neon-lit whiskey frontier along 35th Street which waters the
community’s blue-collar population during White Sox games.
Select Media Festival, held every fall, is staged solely in Bridgeport and emphasizes Lumpen’s liberal
social agenda, which addresses poverty, discrimination and urban blight through artistic media. Version . . .
better reflects Lumpen’s citywide appeal; events are scattered on the South and West Sides, while artists,
visitors and gallery owners from throughout the city flock to Version’s main staging headquarters in Iron
Studios . . . a quaintly refurbished, multi-storied exhibition center and artists’ living space nestled among
the gaunt skeletons of distribution facilities and warehouses abutting Ashland Avenue.
Taylor remarks, “Bridgeport is certainly opposed to the North Side. . . .” . . . In the self-conscious
universe of Version, however, where social progressivism is as prevalent as edgy artwork, the “g-word”
[gentrification] is off limits. “The moment you say that, people’s heads will start spinning around while
they projectile-vomit pea soup,” says Raver Emanuel.
— John Thompson, “The Art of the ‘Neighborhood of the Future’” (2007)
The cultural transformations of Chicago under Mayor Daley II (1989–2011) were in no
small measure a product of applying the central principle of old Chicago politics to this
new “ethnicity.” That principle is, figure out what they want, give it to them, and remind
them where it came from. Hence the bike paths, flower gardens, indie rock festivals, and
postmodern architecture that grace Chicago’s neighborhoods came accompanied by signs
that told you their source: “brought to you by Mayor Richard M. Daley.”7
And this is Chicago! The pork butcher to the world, the city of broad shoulders, is now
more and more a city of scenes that are a complex plurality of overlapping dimensions,
with hipsters and yuppies and fratboys and metrosexuals as much a part of the cultural
landscape as ward bosses and Irish saloons. In Bridgeport, the classic neighborhood base
of the Daley machine, international Chinese artists mingle with the underground artist
children of Polish restaurateurs, “blue-collar Bobos” we might call them,8 who host
exhibitions and performances in their parents’ businesses and in former warehouses.
This diversification of identities and expansion of personal expression reflects a
national pattern. Indeed, we find that one of the strongest predictors of a self-expressive
scene is the percentage of the population reporting multiple ancestries. Yet these
“fragmented” neighborhoods are neither nothing nor nowhere; they have their own types
of scenes, which can be studied alongside the classic ethnic neighborhood, and with
similar tools. In fact, a major theme in some discussions of postmodernism is that there
can be grounded postmodern practices that celebrate irony, boundary crossing, and mixing
categories rather than fixity, closed worlds, and purity. Susan Sontag’s “Notes on Camp”
offered a classic exposition of this form of practice, extended more recently by authors
like Luc Boltanski and Eve Chiapello (2007), who in The New Spirit of Capitalism
associate playful irony with an “artistic critique” of contemporary capitalism that
transforms standardized experiences into (potential) opportunities for authenticity.
Nor are the links between scene and residence exclusive to North America. Economists
Oliver Falck, Michael Fritsch, and Stephan Heblich (2010) demonstrate that German cities
with baroque opera houses were more likely than others to attract highly educated
residents, who stimulated regional growth. They also cite a survey of about 500,000
Germans, which found that for highly educated workers “an interesting cultural scene”
was among the most important factors in their location decision. Similarly, Clemente
Navarro and colleagues (2012) show that scenes matter in Southern Europe as well,
demonstrating that “the creative class” is highly likely to live in Spain’s “unconventional
scenes.”
Box 5.4
Camp is a vision of the world in terms of style—but a particular kind of style. It is the love of the
exaggerated, the “off,” of things-being-what-they-are-not. The best example is in Art Nouveau, the most
typical and fully developed Camp style. Art Nouveau objects, typically, convert one thing into something
else: the lighting fixtures in the form of flowering plants, the living room which is really a grotto. A
remarkable example: the Paris Métro entrances designed by Hector Guimard in the late 1890s in the shape
of cast-iron orchid stalks. . . .
Camp sees everything in quotation marks. It’s not a lamp, but a “lamp”; not a woman, but a “woman.”
To perceive Camp in objects and persons is to understand Being-as-Playing-a-Role. It is the farthest
extension, in sensibility, of the metaphor of life as theater.
— Susan Sontag, “Notes on Camp” (1966, 280)
In sum, in the new Chicago, as in cities worldwide, the differences that make a
difference in choosing between one neighborhood and another have become far more
culturally subtle and wide-ranging. They go beyond but still include the traditionalism and
neighborliness of the pub or parish or the formality of the opera house. Hence our 15
dimensions and their many combinations naturally come into play as crucial drivers of
residential patterns.
Scenes, Amenities, and Population Change
If Chicago precinct captains saw that neighborhoods were becoming defined by the
subtleties of their scenes, it has taken social scientists longer to catch on. Early voices, like
Paul Lazarsfeld or Daniel Bell, who questioned the traditional sociological assumption
that “variations in the behavior of persons or groups in the society are attributable to their
class or other strategic position in the social structure,” (Bell 1996, 37) were mostly
drowned out.9 Manuel Castells’s (1983) The City and the Grassroots marked a major shift
within the post-Marxist urbanist tradition, arguing that contemporary urban social
movements were oriented toward the quest for communities based on “collective
consumption goods” such as public transportation, education, the arts, and culture. From a
different starting point, Terry Clark and Seymour Martin Lipset’s (2001) The Breakdown
of Class Politics showed that classic left-right, union-capital divisions were becoming less
salient politically in many different countries, while matters of taste, consumption, and
quality of life were becoming more relevant.
Clark built on this idea in subsequent volumes. The New Political Culture (1998)
(coedited with V. Hoffmann-Martinot) showed that an increasing number of mayors and
city councils had added lifestyle and consumption issues to the centers of their agendas:
the environment, amenities, gay tolerance, neighborhood aesthetics, and the like. The City
as an Entertainment Machine (2004) followed by pioneering the study of how amenities
drive urban migration, using data from the yellow pages for the first time to show that
counties with more built amenities (like operas and juice bars) had rising numbers of
young people, while older people were increasing in counties with more natural amenities
(mountains, lakes).
Even economists reported examples of amenity-driven migration. Richard Florida’s
(2002) The Rise of the Creative Class popularized this emerging consensus on the power
of consumption rather than only production to drive population changes, adding a
distinctive focus on clusters of artists and gays, dubbed “Bohemian,” as amenities in their
own right, attractive to “the creative class.” And Edward Glaeser’s work on the “consumer
city” argued that population growth was now driven more by what a city offered for
consumption (restaurants, theaters) rather than for production (factories, warehouses)
(Glaeser, Kolko, and Saiz 2001). Florida’s strong statement was reformulated by Clark
and Glaeser (see the summary in Wikipedia’s “Richard Florida” entry as well as chapters
by Florida, Glaeser, and Clark in Clark [2011a, chs. 1, 2, 4, 6, and 7]).
The scope of the shift becomes apparent when we note how even leading proponents of
more traditional Marxian styles of analysis have added more explicit attention to culture in
their concrete writings, for example, on urban development. One case in point is Harvey
Molotch. His earlier Urban Fortunes (1987) (with John Logan) on the “urban growth
machine” stressed business elites as driving urban development by rigging the political
system in their favor. Since then he has softened his stance, and looked to cultural allure,
and not only business and power machinations, as a key force driving urban change. Thus
by 2011 Molotch himself was ready to declare a strong link between “the soul and
migration” and to argue that factors beyond the political-economic are at play in
determining how a place becomes the place it is and whether, and in what direction, it
grows.
Another source of renewed attention to local culture in sociology comes from recent
efforts at the nexus of urban and cultural sociology to rethink questions about purported
“cultures of poverty.” For years after the infamous Moynihan (1965) report was published,
social scientists, for instance, mostly stopped writing about the African American family
—it became too politically sensitive, especially to document its decline.10 Then William
Julius Wilson and Orlando Patterson pioneered work in the 1990s that reintroduced the
centrality of the family to interpret many aspects of black life and culture.11
Box 5.5 The Soul and Migration
People sense . . . that they are more in simpatico with one type of place compared to another, and indeed
with one particular place compared to another. The basis for their preference includes the vast range of
subtle judgments that the sociologists and anthropologists of consumption (including even some critics of
consumption) understand as within the repertoire of active and subtle choice making. We all know, as
sociologists or not, that people are not self-maximizing automatons; they live in part through expressivity
and aesthetic preference. Some regard their very lives as works of art, striving to make them lovely in some
sense. . . . [There is a] link between migration and soul.
This does not mean that “hard” variables are not also at work; it helps to have sewerage and some kind
of economic opportunity in the target destination. And manipulators of the political economy actively
prepare the ground, as best they can, for effective exploitation of those they can attract. But within a range,
migrants’ (and emigrants’) proclivities of style and sentiment come into play (literally, at times, play). And
once in motion, there are mechanisms . . . that continue to reinforce their patterning. Graphic designers and
police have about the same educational levels and similar incomes but their daily routines, consumption
tastes, and voting behavior will differ—as will, pari passu, their destination ambition and how they will
behave once present. Hence . . . New Hampshire and Vermont are matched in educational levels . . . [but]
New Hampshire household incomes are actually substantially higher than those in Vermont. Factors besides
the economic are in play and the standard add-in “cultural” variables, like religion or ethnicity, are not
adequate to understand the selectivity mechanisms.
— Harvey Molotch, “Granite and Green” (2011, 155–59)
The issue continues to inform much discussion about social programs, lifestyle, cultural
change, and more. In the process, “culture” returned to the sociological research agenda,
but not as ostensibly positive or perverse values that attach to distinct groups (e.g., “Irish
values are corrupt”).12 Instead the focus is on particular settings and activities, and how
they do or do not build up important skills, social contacts, knowledge, and abilities. A
person who grows up and lives in a place with high crime, poverty, and few amenities and
services will likely have a distinct, and understandably oppositional, attitude toward his or
her broader society.
Contemporary research has thus turned to local amenities and their potential role in
changing the trajectory of black neighborhoods. Schools, daycare, churches, and
community centers often feature prominently. Ethnographic studies suggest that such
amenities can play key roles in establishing a circuit of neighborhood relationships that
encourage mutual support, information sharing, and respect.13
In this period of intellectual ferment, there have been many names for social
connections based on aesthetic sensibility, like “lifestyle enclaves” or “consumption
communities” or “communities of taste,” as well as for what draws such groups to
particular places, like “cultural ambiance,” “place aesthetics,” or our own “scene.” They
all point toward something common. The style of life that a place makes possible is a key
factor in defining what makes it an attractive place to live; scenes inspire the human
habitat with meaning.14 And in some cases (as box 5.6 illustrates), the sense of belonging
that comes from life in a scene can rival, or at least be mentioned alongside, that which
comes from the most emotionally charged of all human bonds, that of the family—not
unlike how the rise of ethnicity as a source of identity in nineteenth-century Europe drew
its energy from metaphors from the extended family.
Box 5.6 The Scene as Extended Family
When we speak of ownership, we are speaking in an ideological or rhetorical sense, not an economic one.
A city, by its very nature, is not owned; it is shared. Public space is public property. Especially for those of
us—and there are many—unable to afford private property, a condo or house to call our own, public space
is extremely important. Increasingly, our homes are outside: in the streets, on patios, in bars, on concert
stages, in bookstores, in parks. Family extends beyond living room walls and includes the people who are
in your band, who are on your basketball team, who help design your website and who are part of your
burlesque act. The public is private and vice versa, always.
— Jason McBridge and Alana Wilcox, uTOpia (2005, 13)
Standard accounts of urban change, which typically focus more on socioeconomics and
politics, tend to miss the significance of the scene in driving migration. One powerful
example of how important this can be, however, comes in a recent study by sociologists
Jason Kaufman and Matthew Kaliner on the different trajectories of Vermont and New
Hampshire. Throughout the twentieth century, the two states have been quite similar
socioeconomically, and in the beginning they did not differ substantially politically.
But through the early part of the century and especially from around the 1930s on
(Kaufman and Kaliner 2011, 138), Vermont billed itself as a haven for people looking to
live in close contact with nature and art in a generally relaxed tolerant environment. New
Hampshire’s image, by contrast, was business friendly, tourist friendly, individualistic,
with low taxes and easy access to big cities: “Live free or die” is on the state’s official
license plate. Over the years, people from all over moved to the two states, often based on
whether these images spoke to them. Hence Vermont shifted politically, moving from the
right to the left to become the liberal stronghold it is now. New Hampshire remained more
libertarian. One of Kaufman and Kaliner’s main pieces of evidence for the cultural
dynamics of this shift: Vermont has far more Birkenstock stores, vegetarian restaurants,
health food stores, hemp shops, and Ben and Jerry’s; New Hampshire, more Dairy Queens
and Harley Davidson stores.
Home Is Where the Scene Is
All of this implies that a place with a scene that expresses the vibe, the feel, the mood, the
ambiance with which you identify, with which you are simpatico, would be, all things
considered, a more attractive neighborhood to live in than would one that does not. You
should be more tuned into the scenes with which you resonate, and be more motivated,
again all else being equal, to move or stay near one than would somebody whom the scene
leaves cold, or even repulsed. Let us put this general proposition, as well as several more
specific ones, to the test.
Critically Extending Past Work: Zip Codes versus Cities/States, Single Amenities
versus Whole Scenes, Total versus Subpopulations, Mono- versus Multicausality
To do so, we critically extend in a number of ways much of the past work reviewed above.
We have introduced most of these features of our approach before, but they are important
again in the present context.
First, while most research on culture, amenities, and population change analyzes
population changes at the city, county, or even state level, we start from the zip code. This
analytical decision is rooted in familiar experiences. How often does one hear, “I’m
moving to New York State!” or “Wisconsin, here I come!” Maybe sometimes, but
generally states have less psychological relevance in most location decisions than do
cities: “SF or bust!” or “Which way to Austin!” are more common slogans. Even so, there
is so much variation (in scenes, education levels, racial composition, etc.) within cities
(think, for instance, of Staten Island versus Manhattan), that only analyzing the city leaves
us in the dark when it comes to the decision: Where, exactly, in which neighborhood, will
I settle? That is, “in which Chicago neighborhoods would I be comfortable?” To tell which
ones, we need to go down to smaller units.
While it remains important to include larger units, starting from the zip code allows us
to assess the relative importance of small and big (from zip code up to county and state),
and to ask whether, for instance, a city’s average rent, or overall job growth, affects, or
even trumps, the scene-like qualities of the local area in location decisions. This is a
simple point, but it differs from much research that typically investigates larger units and
so is unable even to ask these sorts of questions.
Next, unlike most studies of amenities and population changes, we typically focus not
on one or a few amenities but on hundreds (though we do sometimes examine smaller
subsets to address specific hypotheses about key amenities). These thicker measures can
be analytically critical since the overall cultural character of a place (what our scenes
measures aim to capture) typically changes relatively slowly, but numerous discrete
individuals and amenities move in and out. Thus, many experimental young people may
move to a Greenwich Village, or Wicker Park, or Toronto’s Queen Street West for the
generally self-expressive, transgressive, offbeat, and funky scene. Some stay as they age,
but others move elsewhere when they have children or develop more moderate tastes,
often to different scenes that combine self-expression with different dimensions, as we
will see below. New young Bohemians or hipsters move in, and though particular
businesses may change, these often continue the general ambiance of the scene—a body
art studio opens, a tattoo parlor closes; a Thai-Mexican fusion restaurant closes, an IndianMexican fusion restaurant opens. The scene remains as the particular occupants change.
Yes, scenes do change and move, sometimes dramatically. The migration of New York’s
alternative scenes to Brooklyn is a powerful example. But in the aggregate, they do so
more slowly than do specific individuals and amenities. Scenes are ecological rather than
individual-level phenomena. This is one major theoretical justification for why we
typically treat scenes as independent variables and population changes as dependent
variables.15
Moreover, instead of only analyzing changes in the total population of an area, we focus
on subpopulations such as age groups, college and postgrads, artists, and African
Americans. Simple as it is, this focus on subpopulations goes beyond much urban and
community research, which looks for causes of growth or contraction in the total
population. The problem with this standard approach is that it blinds us to the great
diversity of processes at work behind overall population change, as many subgroups rise
and fall for many different reasons. A city with relatively stagnant total population change
can experience huge gains in some parts and declines in others. Or total population can be
constant while the types of people in a neighborhood dramatically change. Thus it makes
more sense to specify how distinct subgroups behave rather than to posit generalities about
“what (all) people want,” like low taxes or warm weather.
In an ideal (analytical) world, we would be able to go beyond the relatively gross
subcategories of the census, and find out not just how old somebody is or whether she
graduated from college but also what kinds of books she reads and what types of
restaurants she dines in, not to mention her personality. Then we could explicitly weigh
the relative importance of her tastes versus her educational credentials in her location
decisions. Alas, data like these, at a low-enough geographic level, if they exist at all, may
be locked away in the digital vaults of the market research departments of major
corporations.16
While we are therefore stuck with the census categories, we can still do a lot with them,
beyond simply showing, which we do, that there are significant connections between
scenes and where people in different age, ethnic, and educational groups live. Indeed,
there is a reason the census divides up the population the way it does. These categories are
and have been very important ways in which people define themselves and others.
At the same time, the census information can be used to show how scenes open up
cracks within and build bridges across these classic divisions: by showing how, for
instance, the same census groups are sometimes drawn to different scenes, how similar
scenes sometimes appeal to multiple census groups, or how different combinations of
scene dimensions have different impacts on the same census group. While this is all
somewhat abstract right now, we elaborate below.
To do so, we return to our main Core variables, introduced in chapter 4, since they are
relevant to residential as well as economic questions. Total county population is again
important to account for, since many people live in and move to cities where there are
already a lot of people, for all the opportunities—business, romantic, or otherwise—which
that entails. We again include county rent as a proxy for general cost of living and
affordability in the area. Accounting for the college graduate share of the population
allows us to assess the importance of being near educated people in location decisions.
Accounting for the nonwhite percentage of the local population allows us to assess the
degree to which the racial composition of an area shapes where groups live and potentially
moderates the impacts of scenes. Crime is clearly a major factor in location decisions, and
so we again include the same crime data as in chapter 4. The rate at which a county voted
for Bill Clinton in 1992 is a proxy for the area’s overall political orientation at the first
time point in the analysis, which may influence which cities certain groups find hospitable
or not. As in chapter 4, we include a variable for local cultural employment concentration.
This variable can be interpreted as an indication both of the heightened artistic ambiance
that more cultural firms and their staff can add to an area, as well as the job opportunities
that such firms offer. And we again include as part of our Core model the
Communitarianism/Urbanity scene measure, which allows us to ensure that any
connection between a more specific scene or scene dimension is not simply a reflection of
this most common American scene distinction.
To these we add two variables beyond the Core. First is the USDA’s index of natural
amenities (lakes, mountains, etc.), because living close to nature may be an important
consideration for many people, and natural amenities have featured prominently in past
studies of amenities (Clark 2004; Zelenev 2004). Second is a measure of the county
increase in total jobs, which accounts for a question we often receive in conference
presentations: “Sure, the scene might be important when choosing a neighborhood, but is
not the really important decision which city to live in, which is the place generating the
most new jobs?”
All results we report for scenes are net of these other variables, that is, they show the
strength of the connection between the scene and the census group (young people, college
grads, etc.), accounting for, holding constant, or independent, of the education, rent, crime
rate, density, and so on, of the local area. However, since we are concerned with scenes as
one factor among many, and even as the overall character of the place in its entirety,
which includes amenities and people and crime, and so forth, we also often report results
for these other variables as well.
Young People Live in Scenes Where They Can Sow Their Wild Oats
A first set of questions about how scenes shape residential communities concerns the links
between scenes and specific subpopulations: In which types of scenes do which types of
people live? We start with age groups: young people (18–24, 25–34), baby boomers (born
between 1945 and 1965), and retirees (i.e., persons 65 or older). Why age? For a number
of reasons.
For one thing, especially since Florida’s The Rise of the Creative Class, many cities,
officials, and researchers have been interested in the question of what attracts young
people to a given place. The general idea is that with their youth they bring energy,
vitality, openness to and tolerance of new ideas, and a kind of comfort with the growing
diversity that increasingly characterizes American life. And they are often net contributors
to the tax base. Some researchers even speak of the “youthification” of many urban areas
(Moos 2014). We qualify this image below.
For another, whatever baby boomers touch, they change. Wherever they go, they come
in numbers, often with large and open wallets, at least in the aggregate. But of course,
there is much more to the boomer generation than size. Not least is the fact that the
boomers have been in many ways pioneers of consumption (from the Beatles to the hula
hoop), and it is unlikely that their interest in such things would disappear with age.
Third, retirees are growing as a segment of the population. It stands to reason that, at
least for many of them, where to live is an open question, whether downtown near the
opera or in the quiet countryside. And while much of the academic literature focuses on
youth, retirees bring much free time, willingness to volunteer, and often a fair amount of
discretionary income to wherever they settle. They are no longer job-bound, though their
families matter. So detailing what attracts them is important as well to understand how and
why communities are changing.
In what types of places do these age groups tend to live, and where are their numbers
changing? Look at figure 5.2 to find out, which shows the associations of self-expression,
transgression, and their combination with young people and baby boomers both in terms
of their zip code population shares in 1990 and in terms of the difference between their
1990 and 2000 percentages of the population (we return to retirees below).17
Figure 5.2
This figure shows the impact of (YP) self-expression and transgression performance scores, as well as their interaction
term, on six outcomes: (1) percentages of zip code residents 18–24, 25–34, and baby boomers (1990); (2) differences in
the percentages of these same groups between 1990 and 2000. Black circles indicate statistically significant (p < 0.05)
positive associations while hollow circles indicate statistically significant negative associations. Circle sizes are
proportional to the magnitudes of coefficients from a multilevel model, where zip codes are the level 1 units of analysis
and counties are level 2. In addition to these three scene variables, the full model includes the Core: county population,
rent, party voting, and crime rate; zip code percentage college graduates; percentage nonwhite; cultural employment
concentration; and our factor score measure of Communitarianism/Urbanity. Analyses in this chapter add to the Core:
change in total jobs (1994–2001) and natural amenities. All analyses of change variables as outcomes include the
corresponding level in the model (e.g., 1990 level of 25- to 34-year-olds for change in 25- to 34-year-olds, etc.). N is all
US zip codes. More on variables and methods of analysis is in chapter 8 and the online appendix
(press.uchicago.edu/sites/scenescapes).
Figure 5.2 contrasts the three age groups’ relations to the two scene dimensions. In
1990, both 18- to 24-year-olds and 25- to 34-year-olds composed, somewhat surprisingly,
below average percentages of the population in the country’s more self-expressive scenes
(net of the other variables in the model). Population shares of 18- to 24-year-olds were
typically higher in more transgressive scenes, while the 1990 level of 25- to 34-year-olds
was unrelated to transgression. However, from 1990 to 2000, 25- to 34-year-olds did rise
(as a share of the population) in more transgressive scenes—in fact, of all variables in our
model, only total county population was more strongly linked with growth in 25- to 34year-olds than transgression. At the same time, again somewhat surprisingly, 25- to 34year-old growth was unrelated to self-expressive scenes and 18- to 24-year-old growth
was negatively related.
By contrast, 1990 levels of baby boomers were unrelated to transgression or selfexpression. But Boomer population shares rose from 1990 and 2000 in these scenes. As
the boomers aged, they grew more where self-expression was affirmed and transgression
denied. The world of pottery classes and bookshops attracted more boomers than scenes of
tattoo parlors and punk clubs.18
Should we conclude that young adults do not care about, or even resist, self-expression?
No, if we remember that the overall scene includes combinations of dimensions. The
results so far show a dichotomous choice between self-expression and transgression in
isolation. Transgression seems to win.
But what if we combine the two?—not tattoo parlors or art galleries but both together in
the same place. Statistically, one can identify this effect by multiplying two variables
together, making what is called a multiplicative interaction term. Figure 5.2 also shows
results for this interaction term, labeled “transgressive and self-expressive”
Figure 5.3 shows that, even when controlling for self-expression and transgression as
separate dimensions, 18- to 24-year-olds and 25- to 34-year-olds are more concentrated
where self-expression and transgression are combined. Growth in baby boomers by
contrast was lower in such locations.19
Figure 5.3
This figure shows the impacts of 14 variables on two outcomes: (1) percentage of zip code residents aged 25–34 in 1990;
(2) the difference in the percentage of this same group between 1990 and 2000. In addition to the variables listed in the
note to figure 5.1, the model includes four scenes measures (plus Communitarianism/Urbanity, part of the Core): LA-LA
Land, Rossini’s Tour, City on a Hill, and Nerdistan. These scene variables are factor scores based on a principle
components analysis of the 15 scenes dimension performance scores for all US zip codes (summarized in chapter 8). See
figure 5.1 notes for more detail.
These results also show that self-expression is not the sole property of the young. In
fact, Stern and colleagues show that “knowing someone’s age or year of birth provides
very little power in explaining his or her level of arts participation” (Stern 2008, 15).
Moreover, if we look specifically at “Neo-Bohemian” amenities20 (like cafes, art galleries,
etc.), we find (not shown) that these are often located not only where there are more young
people but also where there are more older persons. As this goes fairly strongly against the
grain of much recent research on urban growth and the arts, we have elaborated on this
“gray creative class” elsewhere.21
Adding Multiple Complex Scenes
We can see the diversity of scenes to which people across and within age groups are drawn
by looking not only at self-expression and transgression but also the overall patterns of
scene dimensions.
Recall from chapter 3 that Communitarianism/Urbanity is the most typical US
combination of dimensions. But there are other major complexes into which scene
dimensions frequently combine:22
• LA-LA Land Tinsel is strong in glamour and exhibitionism. Examples of amenities correlated with this scene
include nightclubs, tattooing, health clubs, beauty salons, custom T-shirt shops, body piercing, costume
shops, dance companies, and automobile-customizing services; it has relatively few fishing lakes, hunting
lodges, cemeteries, truck stops, campgrounds, convents, and public libraries. LA-LA Land has a strong
presence in Downtown and West LA, as well as in Chelsea in New York and the Loop and Near North Side
in Chicago.23
• Rossini’s Tour stresses both local authenticity and self-expression. Associated amenities include antique
shops, marinas, fishing lakes, yoga studios, art galleries, used and rare bookstores, coffeehouses, bed and
breakfasts, gardening, and outdoor recreation camps. Fast food, car dealers, truck stops, and churches are
relatively rare. Places such as Sonoma and Marin Counties in California score high on this scene, as does
Greenville, South Carolina.
• City on a Hill features egalitarianism and charisma, and less glamour. Associated amenities include public
libraries, churches, and cemeteries; examples of relatively rare items include equestrian centers, yacht clubs,
ski resorts, nightclubs, travel agencies, private tennis courts, restaurants, health clubs, nail salons,
advertising agencies, art dealers, and interior design. This scene is strongest in the Midwest.
• Nerdistan, a term from Joel Kotkin, combines rationalism and formality. Correlated amenities include
scientific and technical consulting services, legal offices, software publishers, R&D, business associations,
professional organizations, and computer programming services. Examples of amenities that are relatively
rare in Nerdistan include campgrounds, fishing lakes, liquor stores, talent agencies, recreational goods,
antique dealers, tattooing, artists, and fashion designers. It is found more in the West and South.
Scenes Tell Us about Subgroups in Addition to Total Population Changes
Who tends to live near and move to these scenes? Total population grew in two of these
scenes: Communitarianism and Rossini’s Tour (not shown). However, all these scenes are
distinctly linked to specific subpopulations: not all scenes appeal to all people; different
scenes resonate with some rather than others. Which and to whom? Figures 5.3, 5.4, and
5.5 show which scenes are associated with which age groups.
Figure 5.4
This figure shows the impacts of 14 variables on two outcomes: (1) percentage of baby boomers (born 1945–1965) in
1990; (2) the difference in the percentage of this same group between 1990 and 2000. See the note to figure 5.2 for more
details.
Figure 5.5
This figure shows the impacts of 14 variables on two outcomes: (1) percentage of retirees 65+ in 1990; (2) the difference
in the percentage of this same group between 1990 and 2000. See the note to figure 5.2 for more details.
Figures 5.3, 5.4, and 5.5 show proportions of young people, baby boomers, and retirees,
as well as their changes. The figures are sorted by how strongly each variable is connected
to the level of each age group in 1990.
What stands out first and foremost for young people (aged 25–34) is how urbane they
are. They were most concentrated in big cities where crime and rent were high, natural
amenities were low, and jobs were growing; they were in zip codes with relatively strong
cultural industry clusters, high nonwhite population shares, and few college graduates;
they increased more where there were more Democrats.24
Scenes are clearly important factors in accounting for the residential patterns of young
people. Again contradicting the image of coolness as an inherent property of youth,
however, is the fact that young people (25–34) were most strongly linked with Nerdistanstyle scenes of rationalism and formality, and then after that with the generically less
communitarian mix of transgression, utilitarianism, corporateness, state, rationalism, and
glamour. However, they were also likely to be concentrated in LA-LA Land, which mixes
glamour and exhibitionism, and to be increasing in such scenes. Young people were fewer
and declined in a Rossini’s Tour mix of local authenticity and self-expression. Youth, to
use a term from cultural studies, is a multivocal signifier.25
What about baby boomers? Through 1990, boomers were more concentrated in high
rent, Democratic counties, among college graduates and near cultural worker
concentrations, where crime and population were high, natural amenities and nonwhites
were relatively rare, and jobs were growing. Scenes of Urbanity and Nerdistan tended to
have relatively high boomer shares of the population; they made up lower shares of the
population in City on a Hill scenes.
From 1990 to 2000, the types of zip codes where boomers increased most as a share of
the total population were somewhat different. Growth was higher where there were more
college graduates and few nonwhites, but, in contrast to their levels, growth was slower in
Nerdistan and less communitarian scenes, shifting from the historic pattern of 1990 levels.
Boomers moreover significantly increased in Rossini’s Tour scenes. This finding adds
precision to figure 5.3: boomers have shifted not so much into self-expressive scenes
per se but into those that mix self-expression with local authenticity (think yoga studios,
coffee shops, gardening centers, together with art galleries). Boomer population growth
was relatively weak in cultural employment clusters and LA-LA Land, and was unrelated
to natural amenities.
Given their large numbers, this “great aesthetic migration” of boomers to new scenic
pastures like Sonoma, California, or Asheville, North Carolina, may point toward a largely
undocumented reshuffling of the urban landscape. The trend is hard to identify or explain
without a theory of scenes and amenities data. Yet clearly, boomers have been on the
move, and the scene has been a lodestone showing the way. These results underscore a
policy point we stress in chapter 7: what attracts the young and the restless may turn
others off; cities may benefit from a wide array of scenes, beyond LA-LA Land glamour,
especially if the policy goal is to keep those twenty-somethings around as they mature.
And retirees, 65 or older? They made up larger percentages of the population in lower
rent, lower crime, less populous areas with relatively weak job growth and many natural
amenities, fewer college graduates and nonwhites but greater cultural worker
concentration. Scenes in zip codes with retirees had a communitarian feel, a Rossini’s
Tour’s combination of self-expression and local authenticity, a City on a Hill that fuses
egalitarianism with charisma, and Nerdistan’s utilitarianism, corporateness, and formality.
While much of this picture comports with a fairly traditional image of where older
persons would live (a small-town feel near natural amenities, consistent with Clark’s
[2004] finding that older persons tend to live near natural amenities), other aspects point in
a different direction, such as the strong connection with cultural employment clusters. The
classic picture seems to have mostly persisted between 1990 and 2000, but there are
differences. Retirees rose in zip codes with more college graduates and weak LA-LA Land
and Nerdistan scenes.
Artist Concentrations: Not Only about the Rent
These results show that where Americans live is often clearly connected with a specific
type of scene, with a specific cultural and aesthetic feel—even accounting for “harder”
variables like rent, jobs, race, and education. From here, we can see how various scenes
link to other key segments of the population, like artists.
Indeed, if urban analysts have recently discussed youth, they have been positively
obsessed with people working in arts and culture. Much of the focus is economic, for the
reasons in chapter 4.
But there are also more social and community issues linked with artists. Where there are
more working artists, so the argument goes, neighborhood quality of life increases.
Streetscapes tend to become beautified and street life more vibrant; new opportunities for
community connection appear in art classes, studios, and shows.
But there is a dark side to artist growth. Artists are drawn to urban, inner-city
neighborhoods with cheap rents and an air of risk, marginality, and diversity, often linked
to crime and nonwhite persons. As artists work their magic, the neighborhood grows more
attractive. Others, often white, well-off, college graduates, move in. Rents go up, and soon
enough, not only the original inhabitants but also the artists themselves are pushed aside as
ritzy condos and high-end restaurants replace dive bars and grungy music clubs. That is
the standard gentrification story, in a nutshell.
While we cannot observe these processes directly with our data, we can catch some of
them. We can ask, for instance, about where jobs in the arts and culture are most
concentrated, where they have increased, and what characteristics such neighborhoods
have. First, in what neighborhoods do artists concentrate?26 figure 5.6 has the answer.27
Figure 5.6
This figure shows the impact of 14 variables on two outcomes: arts concentration (1998) and change in arts
concentration (1998–2001). These 14 variables are the same as those listed in the note to figure 5.2, except we removed
cultural industry concentration and added change in zip code rent (to account for some gentrification dynamics). Change
is measured as the ratio of 2001 to 1998 levels, and only includes zip codes that had any arts workers in 1998 (whereas
the levels analysis includes all zip codes). We use here a more narrow measure of the arts in contrast to the broader
cultural industry variable in our Core models. The narrow measure includes independent artists, writers, and performers,
musical groups and artists, dance companies, other performing arts companies, theater companies, fine arts schools, art
dealers, and motion picture theaters. We measure arts concentrations as a location quotient, that is, the share of each zip
code’s total labor force that works in the arts compared to the national average. See notes to figure 5.1 for more details.
The arts live up to their general reputation. The strongest predictors of where arts jobs
are concentrated include the percentage of college degree holders and county population
size. Other important factors are LA-LA Land, Urbanity, and natural amenities. Crime
rates and zip code share of nonwhite residents are also positively linked with artist
clusters, as are City on a Hill and Rossini’s Tour.
Perhaps most intriguing here is that four out of five of the country’s most common
combinations of scenes dimensions, even when controlling for one another and the other
variables in the model, are positively and significantly linked with concentrations of
people who work in the arts and culture. Artists are not only found in scenes of Urbanity,
glamour, and exhibitionism, but also in Rossini’s Tour mixes of self-expression and local
authenticity and City on a Hill’s mix of egalitarianism and charisma. “Artist” is a far from
homogeneous category; its members range from countercultural rebels to church choir
leaders to desert landscape painters. This internal differentiation shows up in their
concentration in very distinct scenes and locales.
And what about rent, the usual centerpiece of the gentrification story? Our results show
arts employment concentrated in higher rent areas. At the same time, we find no
relationship between arts clusters and change in rent between 1990 and 2000.
This more complex picture of arts clusters persists if we look at places where artists
grew more concentrated from 1998 to 2001. Admittedly, this is not a big enough time
period to draw general conclusions.28 Moreover, only some US zip codes have any arts
employment whatsoever (about 10,000), and there is little difference between where
growth occurred and where concentrations were already high, relative to the country as a
whole. Artists, contrary to some popular narratives, do not appear to move incessantly into
new terrain. It is thus useful to look at only those zip codes where some arts jobs are
present, and the factors related to increased concentration of the arts therein (measured as
a ratio of the 2001 to the 1998 location quotient).
The results (in figure 5.6) are intriguing. Arts employment concentration increased in
smaller counties with less crime, and in zip codes with more college graduates and smaller
1998 artist clusters. County rent was insignificant, as was change in zip code rent. Three
of the five scene factor scores, however, were significant: arts jobs concentrated more in
stronger Communitarian and Rossini’s Tour scenes and weaker Nerdistan scenes. That is,
not the most urbane, populous, or low rent areas, but areas with scenes that include local
authenticity, neighborliness, tradition, and self-expression.
Urban analysts Carl Grodach and Michael Seman come to a similar conclusion about
going beyond the standard variables in their analysis of the cultural sector during the Great
Recession after 2007. They find
no clear evidence that artists or other cultural sector workers are increasing in affordable, older industrial
metros like Detroit and Cleveland whether due to migration from more established cultural hubs, as has been
widely reported in the popular media, or otherwise. Both of these regions, which possess below average
concentrations of cultural sector employment, have endured declines during the recession not only for cultural
occupations as a whole, but for artists in particular. Altogether, the correlation coefficient for cost of living and
cultural sector employment growth is weak (.122) and not statistically significant. (Grodach and Seman 2013,
19)
Even in a time of general economic recession, cost of living is a relatively weak
determinant of growing arts employment.
And this all stands to reason. Take Chicago’s Wicker Park as an example, one of the
paradigm cases of artist-led neighborhood change. Measured against the average US zip
code, rent in Wicker Park was likely never low—if low rent was the issue, there is always
Toledo. Of course, rent matters at the margins, but so does much else. What Wicker Park
had, like Toronto’s West Queen West or Brooklyn’s Williamsburg, was relatively close
proximity to existing artist networks, relatively easy access to downtown (for gigs and
jobs and other opportunities), a certain sense of dangerousness and excitement (like
prostitutes and drug dealers on the corner), and a base of divey, dingy amenities (like bars
and restaurants) that appealed to Bohemian images of the starving artist—along with
somewhat lower rents than many other North Side neighborhoods.
This may not dramatically alter the overall gentrification story, in that once arts
establishments arrive the scene may change in ways that invite new residents. But it does
suggest that a one-track model, with simple economic and demographic forces driving
inexorably from cheap-rent-seeking artist pioneers to their yuppie successors, is too
simple. As we saw in chapter 4, for instance, Bohemian scenes lead to job and population
growth in more traditional communitarian cities, but not as much in more urbane cities,
where there already are many artists and an arts-friendly social environment.
The point is not that the arts sector “never” cares about rent and “does not” initiate
gentrification; we do not want to replace one unidimensional theory with another. It is
simply that there are many variables and variants at work. The question is when, where,
and why some lead and others follow, and vice versa.29
And there are many more local variants than the standard story would admit. Thus,
strong ethnic neighborhoods may resist (or modify) the “first” stage of gentrification by
controlling access to housing or making sure that their (sometimes) artist children get first
crack, as in St. Louis’s (Irish) “the Hill” neighborhood or Chicago’s (Irish and Polish)
Bridgeport. Politically organized arts advocacy groups can (sometimes) lobby city
government to keep a foothold in the neighborhood even after new nonartists arrive (as in
Toronto’s West Queen West). Arts groups can work with government agencies to provide
jobs to local residents in their offices (as Deborah Leslie and Norma Rantisi document in
the case of Cirque du Soleil in Montreal’s Saint-Michel neighborhood). And “social
preservationists,” as documented by Japonica Brown-Saracino, sometimes organize to
preserve the historic human ecology of neighborhoods even as gentrifying newcomers
move in. Many of these variants and more are documented by Grodach and Silver (2012)
in The Politics of Urban Cultural Policy: Global Perspectives.
Bronzeville and Beyond
Bronzeville, as we saw above, embodies some core cultural dimensions central to many
African Americans: the biblical hope for a world better than ours, based in the equality of
all persons before God; the charismatic presence of the fiery preacher, the musician, or the
great athlete. At the same time, these are joined by energetic nightlife, bright fashion,
dance, innovative music, and a playful flamboyance in dress and appearance, mixed with
an often-critical and countercultural stance toward mainstream American society and
culture. This combination of historic links to deep religious and cultural currents in
African American history together with emergent scenes of wide-ranging entertainment
options and cultural facilities surely played a role in Bronzeville’s recent and relatively
dramatic growth, led especially by middle-income African Americans.
But how unique is Bronzeville?
Figure 5.7 shows that Bronzeville is far from the exception. Rather, it looks more like a
paradigmatic instance of a broader pattern. In 1990, America’s neighborhoods with higher
black percentages of the population tended to be in Democratic counties with relatively
high crime, weak job growth, and few college graduates in the zip code. Such
neighborhoods often had scenes that evoked classic prophetic biblical themes—the
egalitarianism, neighborliness, tradition, and charisma characteristic of Communitarianism
and City on a Hill scenes—as well as the rationalism and formality that characterize
Nerdistan. However, between 1990 and 2000, African Americans shifted away from
scenes of Communitarianism (even if in 2000 black population shares remained higher in
Communitarian than Urbane scenes); at the same time they grew in the LA-LA Land mix
of glamour and exhibitionism while continuing to increase in City on a Hill.30
Figure 5.7
This figure shows the impact of 13 variables on two outcomes: (1) the percentage non-Hispanic black residents in 1990
and (2) difference in in the percentage of this same group between 1990 and 2000. These 13 variables are the same as
those listed in the note to figure 5.1, except that percentage nonwhite was not included as a predictor.
Box 5.7 Confessions of a Black Gentrifier: When Demographic Change
Doesn’t Involve Color
If you ask Aisha Moore about gentrification, her first inclination is to scoff. Moore, a black resident of
Congress Heights, says her Ward 8 street is “100 percent black” and that’s not likely to change soon.
“Nobody leaves,” she jokes. “On my block, if new people bought a house, it’s because an old lady died.”
Yet Moore isn’t from D.C. and has only lived in the city since 2002, after she finished an undergraduate
degree at the University of California at Berkeley. In 2004, her boyfriend bought a house in Congress
Heights and she moved in with him in 2009.
Which, by every metric except one—skin color—makes her as much of a gentrifier as the young white
residents unloading moving vans near U Street NW every weekend. As we talk, Moore says she’s frustrated
by the dozens of stories that feature handwringing over D.C. becoming “less black,” because they paint an
incomplete picture. “I get it, in terms of numbers, but it’s annoying. The story over here, east of the river, is
all about black gentrification,” she says. “Black people are moving back to Anacostia and the Congress
Heights area.” . . . “There are different types of people here, but that doesn’t water down the chocolate,”
she says, with a laugh. . . .
“Gentrifier” can’t be equated with “white person.” After all, most poor people in this country are white
(though it’s definitely a numbers game; whites are still less likely to be poor than blacks and Latinos—there
are just more of them). The gentrifier is a person of privilege, and even if she doesn’t have much money,
she’s got an education and a network of friends who are striving like she is, and she has the resources to at
least try to get what she wants. . . .
Living in Columbia Heights, Chris Wallace feels conflicted. His reception in the neighborhood varies by
what he’s wearing. If he changes out of his suit and into sneakers and jeans after heading home from his job
as a mortgage loan officer, getting a drink at a local watering hole, now overrun with young professionals,
can feel uncomfortable. But it cuts both ways. “Even the younger people of color in the neighborhood,
how, what, or if they speak to me depends on what I’m wearing,” he says. . . .
“I’m a black male in D.C. and I have never been to jail and I have a job. I can’t help but be present to
that,” Decker Ngongang says. He describes a recent outing when he took the day off from work: “I walked
to the Starbucks at 14th and Irving and there may have been 100 black males that I passed who were doing
nothing in the middle of the day.” It’s frustrating, he adds. “A lot of my black male peers are lost
sometimes. What the hell do we do?” . . .
Ngongang deals by finding “little things” he can do, like talking to kids in his neighborhood, and using
his seat at a table with other non-profits to help them understand the context underperforming students are
living in.
— Shani O. Hilton (2011)
These results fit broadly with the notion of the “the new great migration” (Frey 2004),
where many African Americans are moving away from declining Rust Belt areas and into
major southern metropolises, like Atlanta and Memphis, and to many suburban areas.
However, our results are broader than this: if we add the South to our model as a control
variable, we find that, while black population shares increased in the southern zip codes
(between 1990 and 2000), the impacts of scenes on African American migration were not
altered. Southern or not, zip codes with concentrations of cultural industry workers, scenes
of Urbanity, egalitarianism and charisma, glamour and exhibition, saw increases in
African Americans—and this, again, independent of rent, education, population, crime,
and other variables in our core model.31
A Great Divide?
Much academic research on population shifts and gentrification is by demographers and
economists who are traditionally insensitive to more holistic and cultural factors like
scenes. The strength of the above results, however, suggests that analytical attention to
scenes and amenities has much to offer. And not only to them.
The American media and many public intellectuals often invoke themes of division,
separation, and fracture among American residential communities. Conflict is news;
nonconflict is boring. What are the main themes and how grounded are they?
Commentators stressing division come from across the political spectrum. In Coming
Apart (2013), conservative Charles Murray traces a cultural division of American
neighborhoods. On the one hand are “superzips” full of college graduates who maintain
classic American civic and family values while leading culturally bubbled lives set apart
from their working-class compatriots; on the other are working-class communities where,
he argues, these virtues have weakened and positive role models are rare. This division, he
suggests, is reinforced by the fact that each group has its own distinct consumption and
lifestyle habits, with, for instance, college graduates favoring foreign films and noncollege
graduates favoring Hollywood blockbusters. Moderate Bill Bishop’s The Big Sort suggests
a related kind of division: as Americans move more and more based on lifestyle
preferences, they end up increasingly sorting themselves residentially by politics. Liberals
go to where the Starbucks, organic grocers, yoga studios, and Apple stores are;
conservatives go to where there are churches, gun shops, and NASCAR. The result is
intensified partisanship and mutual misunderstanding, as fewer people bump into those
others from the other side of the aisle in their day-to-day neighborhood interactions.
Similarly, Richard Sennett (2012), a man of the left, argues in Together that Americans are
losing touch with “the craft of cooperation,” as “democratic rituals” of listening and
discussing give way to conflict and a tribal us-versus-them attitude throughout society.
This sort of rhetoric of loss, conflict, decline, division, and fracture is as old as America
itself, making one wonder when exactly the unified, coherent time before the current crisis
of community was. An alternative sees community ties as multiplex. Both conflict and
consensus are present at the same time.
This more mixed picture is what sociologists Claude Fischer and Greggor Mattson
(2009) found when they reviewed decades of research on the question, is America
fragmenting? They found increasing ideological polarization among political elites and
activists since the 1970s but more commonality in the general electorate—and nothing
like the level of past animosity that led to deep conflagrations like the Civil War. Race and
ethnicity remain strongly correlated with divergent life chances. And yet racial residential
segregation, while still high, has been decreasing in recent decades; racial intermarriage,
while low, has been increasing. There is evidence of proliferating cultural styles and
options, and more wide-ranging, “omnivorous” tastes; but whether this amounts to
fracture or simply plurality is unclear. The most rapidly increasing disparity is in
education, as college-educated persons have grown more likely to intermarry, to live in the
same neighborhoods, and to share common tastes.
Box 5.8 “Morality in an Age of Contingency”
I will not lament a process of ongoing fragmentation, of the loss of all values in our time, of the
disappearance of community or trust or commitment or the social significance of character formation. Such
jeremiads are so common in current debates about values and morality that they constitute a rhetorical
genre of their own—both in the social sciences and in cultural criticism. They can be found in conservative
as well as in progressive versions. The mere fact of their being a genre of their own can already sensitize us
to the schematizations and narrative restrictions imposed by this genre.
When the American historian Thomas Bender searched American historiography to locate the exact date
of the triumph of individualism and materialism over the ideals of Puritan community life, he discovered
that such a claim has been made for practically all points in time since 1650. Desperately he asked: “How
many times can community collapse in America?” (1978: 46). Similarly, we should ask ourselves when the
time before the alleged contemporary fragmentation of society is said to have been—and whether we really
do justice to contemporary changes if we constantly force them into the framework of loss and decline.
— Hans Joas, “Morality in an Age of Contingency” (2004, 392)
Starting from this more tempered view suggests some general propositions about how
amenities might or might not correlate with America’s major social divisions, in particular
education and race. On the one hand, we would expect certain types of amenities to have
relatively narrow geographic and demographic reach and to thus be relatively strongly
correlated with educational and racial residential concentrations. On the other, these
correlations should be only moderately strong. We could add that there should be certain
types of amenities that have broader appeal, extending into both America’s more- and
less-educated neighborhoods, as well as into areas in which people of diverse races reside.
To examine these general propositions more precisely, we shift from more abstract
performance score measures of scene dimensions to specific amenities, selecting four
types to assess the lines of conflict suggested by standard commentaries. The first two
capture types often discussed as conflicting: “New Age” lifestyles versus conservative
evangelical Christianity. The second two are more widely shared: popular culture and
martial arts. Below we discuss each of these types in detail, and measure them with
indicators from our amenities database. Analyzing their location offers insight into the
types of practices and experiences that are more broadly shared or more narrowly pursued
across American communities. It also points toward a more ecumenical conception of
religious-ethical organizations: churches compete and commingle with other cultural and
leisure options—arts, sports, music, yoga, karate, and more—as parts of the wider scenes
that people may choose to join, defining their allegiances and animosities in the process.
Two major themes emerge in the results. On the one hand, many Americans seem to
live in scenes apart: whites and college graduates near New Age amenities; nonwhite and
less-educated near evangelical churches. On the other hand, these differences are less
hard-and-fast than they might first appear: popular culture and martial arts seem to bridge
the apparent New Age–evangelical cultural divide.
New Conservative Churches: Racial Bridging, Educational Divide32
A major and consistent finding in the sociology of religion—confirmed again in Putnam
and Campbell’s American Grace—is that, especially since the 1960s, membership and
participation in mainline churches has declined. By contrast, conservative evangelical
Christianity has been ascendant.
American popular discourse links the rise of conservative evangelical Christianity to the
religious right and Moral Majority. Because these movements are connected to the
Republican Party, with a reputation for not welcoming ethnic diversity, some draw the
inference that evangelical churches are populated by less-educated whites. Their strict
sexual morality is then construed as a traditional reaction against the tidal wave of
modernity, in its many aspects, from individualism to diversity.
There are many grains of truth to this. In fact, the academic literature often reports that
religiously conservative churches, like Southern Baptists, are historically linked to racially
segregated worship and opposition to government assistance to African Americans. And,
as we show in chapter 6, the evangelical Christian percentage of a county’s population is
one of the most powerful ways to predict whether it votes Republican or Democratic.
Accordingly, evangelicals have figured prominently in many of the debates about
America’s culture divide. Yet the story is more complex.
One of the most significant religious trends in the second half of the twentieth century
has been a truly global growth of conservative Protestantism, not only in the United
States. Growth has been strongest among new or historically marginal strains, such as
Pentecostalism. The evangelical movement in America is just one part of this bigger
surge, which involves huge numbers of conversions in Latin America, Africa, and Asia
(especially Korea). Synthesizing research on this worldwide movement, one of the leading
sociologists of religion, David Martin (2005), concludes that the rise of Pentecostalism is a
distinctively modern religious phenomenon, one centered on ecstatic personal experience
and the charismatic leaders who help people get there. He further suggests that the rise of
Pentecostalism in Latin America especially has fostered an individualistic ethos of
personal discipline and cultivation, connected with greater community leadership roles for
women and heightened demands for sobriety and family commitment from men.
In the United States, these “new line conservative” churches, or “New Cons,” often
understand themselves as outsiders, operating at the margins of the old-guard Protestant
establishment. Many of them actively portray themselves as racially neutral, operating
beyond or outside the cleavages that have traditionally divided American society. They
often include enthusiastic or charismatic worship styles, replete with rock bands and
multimedia performances, that help break down traditional social norms about who should
associate with whom (cf. Collins 2008; Dougherty and Huyser 2008; Marti 2009). Their
combination of individual fervor, charismatic leaders, and egalitarian visions of equality
before God, along with strict adherence to divine authority, carries forward the biblical
tradition of the City on a Hill in a contemporary context.
These New Cons resemble what Max Weber called inner-worldly activists:
missionaries, an army of God, out to reshape the world in His image. Accordingly, many
press their members to invite diverse guests to their services. They establish branches in
inner-city neighborhoods and actively recruit new members from all races. Nobel laureate
economist Robert Fogel has called this upwelling the “fourth great awakening” of
evangelical fervor in American history. The preceding three he links with the Revolution,
abolitionism, and the concern with material and gender equality that led to the New Deal
and women’s suffrage; this one he links with a societal move toward concern with the
distribution of “spiritual” rather than “material” goods.
Box 5.9 Can Megachurches Bridge the Racial Divide?
One Sunday last fall, Bill Hybels, founder and senior pastor at the Willow Creek Community Church in
Chicago’s northwest suburbs, was preaching on the logic and power of Jesus’ words “Love thine enemy.”
As is his custom, Hybels was working a small semicircle of easels arrayed behind his lectern, reinforcing
key phrases. Hybels’ preaching is economical, precise of tone and gesture. Again by custom, he was
dressed in black, which accentuated his pale complexion, blue eyes and hair, once Dutch-boy blond but
now white. Indeed, if there is a whiter preacher currently running a megachurch, that man must glow.
Yet neither Hybels’ sermon, nor his 23,400-person congregation, is as white as he is. Along with Jesus,
he invoked Martin Luther King Jr. Then he introduced Shawn Christopher, a former backup singer for
Chaka Khan, who offered a powerhouse rendition of “We Shall Overcome.” As the music swelled, Larry
and Renetta Butler, an African-American couple in their usual section in the 7,800-seat sanctuary,
exchanged glances. Since Hybels decided 10 years ago to aggressively welcome minorities to his lily-white
congregation, Renetta says, few sermons pass without a cue that he is still at it. “He always throws in
something,” she says. She’s been around long enough to recall when this wasn’t the case. . . .
. . . [I]n some churches, the racial divide is beginning to erode, and it is fading fastest in one of American
religion’s most conservative precincts: Evangelical Christianity. According to Michael Emerson, a
specialist on race and faith at Rice University, the proportion of American churches with 20% or more
minority participation has languished at about 7.5% for the past nine years. But among Evangelical
churches with attendance of 1,000 people or more, the slice has more than quadrupled, from 6% in 1998 to
25% in 2007.
Call it the desegregation of the megachurches—and consider it a possible pivotal moment in the nation’s
faith. Such rapid change in such big institutions “blows my mind,” says Emerson. Some of the country’s
largest churches are involved: the very biggest, Joel Osteen’s Lakewood Community Church in Houston
(43,500 members), is split evenly among blacks, Hispanics and a category containing whites and Asians.
Hybels’ Willow Creek is at 20% minority. Megachurches serve only 7% of American churchgoers, but they
are extraordinarily influential: Willow Creek, for instance, networks another 12,000 smaller congregations
through its Willow Creek Association. David Campbell, a political scientist at Notre Dame studying the
trend, says that “if tens of millions of Americans start sharing faith across racial boundaries, it could be one
of the final steps transcending race as our great divider”—and it could help smooth America’s transition
into a truly rainbow nation.
— David Van Biema (2010)
A significant, but not uncontested, body of research suggests that new conservative
churches do in fact often reach across racial divides. Thus, Robert Putnam found that
evangelical Protestant congregations are more likely to be racially diverse than are liberalmoderate, mainline Protestant ones.33 Michael Emerson found that large evangelical
congregations had “dramatic growth” in racial diversity between 1998 and 2007: only 6
percent of such congregations were classified as ethnoracially diverse in 1998 but 25
percent were by 2007. Almost 20 percent of American Latinos are now evangelical
Protestants. Similarly, others (such as Joseph Yi) find that racial diversity is especially
pronounced among New Cons—those new or less-established strains of evangelical
Protestantism, including the typically “nondenominational” megachurches, that are not
affiliated with the more-established Baptist, Lutheran, Methodist, or Presbyterian
denominations.34 As we note below, we too find that conservative evangelical churches
are more strongly associated with racially diverse neighborhoods than are mainline
Christian churches.
There is another side to the growth of the conservative evangelical movement, however.
New conservative churches have sometimes been more successful than other American
churches in reaching across the country’s racial cleavages. But the evangelical
commitment to strict moralism and literalist adherence to biblical authority tends to fall
flat among college graduates, who are, on average, liberal in morals and relativist in
culture—though these sorts of averages can of course mask internal variation.
These general propositions suggest some specific empirical generalizations, which we
pursue below: neighborhoods with many New Con churches should have (a) higher levels
of overall racial diversity, (b) higher nonwhite shares of the local population, and (c) lower
college graduate shares of the population.
New Age Spirituality: New Spiritualities and Divisions
Resistance to the evangelical biblical message from the most educated segments of
American society has its own logic. Indeed, new line conservative evangelical
Protestantism was not the only religious movement, or even the best known, at least in the
popular discourse, to gain strength in the ferment of the 1960s. There were also the
hippies, who sought new modes of consciousness, an enlightened religion of Love, and a
New Age of Aquarius.
College campuses were key incubators for the new spiritual ideas that emerged from the
1960s counterculture. Of course, not all campuses were hotbeds of Free Love, but places
like Berkeley, Ann Arbor, and Columbia, among others, were major launching pads. And
the country’s most enduring center of New Age spirituality, the secluded Esalen Institute
on California’s rugged Big Sur coastline, was founded by two students from Stanford’s
comparative religion department. There they found behind all the world’s religions—East
and West—a common Divine Spring, which goes beyond any particular authorities,
teachers, and dogmas, flowing through All Being.35
Box 5.10 The Essential Lingua Franca of the New Age: Self-Spirituality.
The great refrain, running throughout the New Age, is that we malfunction because we have been
indoctrinated—or, in the New Age sense of the term, been “brainwashed”—by mainstream society and
culture. . . . To live in terms of such mores, inculcated by parents, the educational system and other
institutions, is to remain the victim of unnatural, deterministic and misguided routine. . . .
Perfection . . . cannot be found by tinkering with what we are by virtue of socialization. Neither can it be
found by conventional (political, etc.) attempts at social engineering. Perfection can be found only be
moving beyond the socialized self . . . To experience the “Self” itself is to experience “God,” the
“Goddess,” the “Source,” “Christ Consciousness,” the “Inner Child,” the “Way of the Heart,” or, most
simply and, I think, most frequently, “inner spirituality.” Experiences of the “Higher Self” . . . stand in stark
contrast to those afforded by the ego. The inner realm, and the inner realm alone, is held to serve as the
source of authentic vitality, creativity, love, tranquility, wisdom, power, authority and all those other
qualities which are held to comprise the perfect life.
— Paul Heelas, The New Age Movement (2003, 18–19)
Perhaps the central feature of the new spiritual awakening was a rejection of authority
and a concomitant turn to the self. Each of us must find our own personal way to bliss;
nobody can do it for us. “Outside” and “external” authorities cannot show the way. They
are at best signposts whose directions must be individually tested; at worst, stumbling
blocks seeking to replace your own experience, your own journey, with dead letters,
secondhand reports, and crushing conformism. As sociologist Paul Heelas puts it, “If there
is too much external authority—theistic, traditionalized, polytheistic—one can conclude
that one is no longer with the New Age” (2003, 25).
Just as important to the New Age is rejecting traditional, especially Christian,
puritanical attitudes toward the body. The body is not a seething tempest of sin and
temptation to be dominated, mastered, and controlled. Rather, the body “knows”; its
impulses and instincts are the seeds of meaningful attunement to the world; they must be
generously cared for, cultivated, awakened, released, loved. Kripal notes that the Esalen
Institute was a pioneer in numerous novel bodily practices, not only yoga and body work,
but also jogging.
These two elements—a search for sources of spirituality beyond Western Christianity
and in the body itself—made New Age spirituality highly open to Eastern imports, in
particular Yoga. Of course, much in Eastern religious tradition—for instance, the authority
of the guru—did not fit comfortably with self-spirituality. Still, enough did, and much was
reinterpreted in the new American context.
Particularly attractive, as Heelas argues in discussing the growth of Buddhism in the
United Kingdom, were “forms of eastern spirituality which emphasize world-rejection”
(1986, 55). “World-rejection” is a term that comes from Max Weber, and New Age
spirituality rather closely approximates what he called the “passive-otherworldly” way of
rejecting “the world.” Rather than actively working in the world to change it, one must
“let it be,” retreat to some sanctuary, meditate, contemplate, and wait for divine revelation
to come to you. Hence the New Age movement flourished in the mountains of the
California coast and the deserts of New Mexico.
This “self-spirituality” of course has deep roots in American culture, as does the mixing
of East and West. New Age ideas clearly evoke themes that carry forward ideas from
Emerson to Whitman, many of which congeal in this volume’s notion of individual selfexpression. Indeed, in the late nineteenth century, Indian Vedic and Yoga philosophies
entered the United States in the salons of New England literati, attended by the likes of
William James.36 His “Gospel of Relaxation” adumbrated key themes that would later
animate the New Age movement as it spread from Cambridge salons to Whole Foods
message boards (Bender 2010, 106–12).
Box 5.11 Mixing East and West in the New Age
Dick [Richard Price, one of Esalen’s founders] received the name Geet Govind from the guru (through the
mail) and began planning what would become a month-long trip to Poona. This was big news at Esalen, as
it seemed to suggest that one of the basic ground rules was about to be broken, or at least seriously tested.
“No one captures the flag.” No gurus. But now there was a guru, and one of the founders at Esalen
appeared to be submitting to his teachings. . . .
That didn’t happen. Dick spent the first two weeks in the ashram’s meditation facility, where things went
reasonably well. Then he moved into the encounter group sessions and participated in a session with an
English psychotherapist. . . . Still well enough. Then in a session next door, a woman got her leg broken in
a fight, apparently generated by the group session. This upset Dick deeply. What sealed his rage, however,
was a second scene involving Rajneesh himself. Shortly after the broken bone, a woman stood up in the
question-and-answer session and asked the guru about the violence. She questioned whether this was really
necessary. According to Dick, Rajneesh not only did not respond to the question; he turned on the woman
and tried to intimidate and shame her into silence. That was it for Dick. . . .
Later, he wrote to Time . . . “Rajneesh . . . can speak brilliantly of the transformative possibility of human
life. . . . However, the ashram ‘encounter’ group is an abomination—authoritarian, intimidating, violent—
used to enforce conformity to an emerging orange new order rather than to facilitate growth. . . . I am
content to be known as ‘Richard Price’ rather than as ‘Geet Govind.’”
— Jeffrey Kripal, Esalen (2007, 364–65)
Since its rapid growth in the heady days of the 1960s, various forms of “being spiritual
but not religious” have flourished and spread (Wuthnow 2007). Heelas (with collaborator
Linda Woodhead) estimates that, as of 2001, upwards of 900,000 people in the United
Kingdom are active in “the holistic milieu” of acupressure, astrology, Eastern religion,
yoga, shiatsu, and the like (2006, 47). Data are less precise in the United States, but their
estimate is somewhere between 5 and 20 million American holistic practitioners.
This growth, however, has not extended much past the initial milieu in which the New
Age was born. Heelas and Woodhead’s own survey of a small British town shows this.
They find that the spiritual revolution has mostly been restricted to white, (now) middleaged women who work in people-oriented professions. Other studies have yielded similar
results, finding that yoga practitioners are mostly higher-income, highly educated, white
women (Birdee et al. 2008), and that “mind-body-spirit” activities in the Boston area are
practiced disproportionately by people with high levels of education, with around 90
percent holding a college degree, and 70 percent of yoga practitioners in particular holding
postgraduate degrees (Oh and Sarkisian 2012). Our results (below) also suggest that the
New Age tends to be strongly correlated with education.
This type of growth pattern is in many ways implied by the very inward, passive,
meditative character of New Age spirituality. For if unique personal self-expression is the
gold standard, it is imperative that nobody be “forced” to join, that devotees not be
commanded or ordered to do missionary work, to reach out to people who may not “want”
to be saved. Better to be a beacon of hope, leave the light on—or be the light—and be
open to anybody ready to listen who might walk through the door. While there is a
spiritual nobility to this, one of its practical, social consequences is that people who are
not already disposed to the New Age message are relatively unlikely to respond to it.
Box 5.12
The American over-tension and jerkiness and breathlessness and intensity and agony of expression are
primarily social, and only secondarily physiological, phenomena. They are bad habits, nothing more or
less, bred of custom and example, born of the imitation of bad models and the cultivation of false personal
ideals. . . .
. . . We must change ourselves from a race that admires jerk and snap for their own sakes, and looks
down upon low voices and quiet ways as dull, to one that, on the contrary, has calm for its ideal, and for
their own sakes loves harmony, dignity, and ease. . . .
. . . Unclamp, in a word, your intellectual and practical machinery, and let it run free; and the service it
will do you will be twice as good.
— William James, “The Gospel of Relaxation” [1899] (1911, 59, 65, 70)
Box 5.13 Mystically Zooming around without Touching
Paula interrupted, “Yes—that was really great. When we are asked to imagine a person, I thought of
George W. Bush. I always think of him as a child, like a little boy, immature and childish. So when Cathy
said to send him love, I thought of him as a baby and sent my love to him as a child. But also, when she
said that we should send our love to the people of Iraq, it was really vivid, I felt like I was zooming in. I
actually saw a mother and a child together, and she was holding the child in front of what looked like their
house. . . .”
. . . While the mystics gathered in the space of the chapel were hoping for peace and justice, and Cathy’s
visualization led us through familiar tropes of critique of American foreign policy and war-mongering, the
entire ritual reproduced a spiritualized imperialism, where those in the United States could travel quickly
and effortlessly to other parts of the world, and lift up both spiritual and “real” women and children from
the lock of spiritual and political tyranny, enter into others’ hearts, and then return untouched to the
familiar. The worst that one could suffer was a “prick” of an evil heart, but even this terror could be
overcome by a protective shield of mystical light.
— Courtney Bender, The New Metaphysicals (2010, 178, 180)
Nevertheless, some practices, especially yoga, have made headway among American
Christians. The more popular Hatha variants stress health and fitness more than other
“mind-body-spirit” practices do (Oh and Sarkisian 2012, 301), helping minimize potential
cultural clashes with Christian teachings. Indeed, the “Christian yoga” movement aims to
actively integrate Christian faith with yoga (Alter 2003; Cullen-Mahtomedi 2005; also cf.
Knaster 2011; Morris 2010), and yoga classes have become more common at local
YMCAs and some mainline churches. Brooke Boon, a conservative Christian, founded
and marketed “Holy Yoga,” including 475 certified instructors in 10 countries (C.
G. Brown 2013a, 45–46). Self-expression is by no means antithetical to religious
communities, Christian or otherwise.
But these efforts to integrate the self-expressive orientation embodied in yoga and New
Age practices into contemporary American Christian practice sometimes meet strong
resistance from conservative Catholic and evangelical elites. In 2003, the Vatican and the
Southern Baptist leadership flatly rejected New Age beliefs and practices, including some
forms of yoga (Stammer 2003). And Mark Driscoll, pastor of Seattle’s hip, evangelical
Mars Hill megachurch, denounced yoga as “demonic,” arguing that it is impossible to
disconnect yoga’s pantheistic spirituality from its physical techniques (Driscoll 2011).
Yoga’s disputed status informs vocal debates over its incorporation into the public schools.
A 2013 legal battle in Encinitas, California, pitted supporters who emphasized the
health/fitness benefits for children, such as physical exercise, mindfulness, and stress
relief, against opponents (including the National Center for Law and Policy, a
conservative Christian legal defense organization) for whom the practice was intrinsically
religious and hence not a permissible part of a public school curriculum (C. G. Brown
2013b).
While the New Age has certainly expanded from the Cambridge séances that William
James attended, it nevertheless faces barriers, especially from those Americans most
committed to theologically conservative and traditional forms of Christianity. Enduring
images of New Age practices as esoteric and antithetical to Christianity are thus a cultural
mechanism that reduces its acceptance among conservative Christians. Much of the
material and human resources of religious conservatives in low-income neighborhoods,
from church basements to volunteers, become less likely to be available to New Age
entrepreneurs looking to expand their operations. Moreover, blacks and Hispanics, and
less-educated Americans, are more religiously conservative and thus less likely to demand
New Age activities. That is, in less-educated and nonwhite neighborhoods, New Age
amenities tend to lack both supply (teachers) and demand (students).
Clear empirical implications for the typical locations of New Age amenities thus follow
from their historically grounded situation in American culture. New Age amenities should
be relatively less numerous and more concentrated than New Con churches, and the
overlap between New Age and New Con should be relatively low. Neighborhoods with
high numbers of New Age amenities should be less racially diverse, and higher shares of
their local populations should be white and have college degrees.
Popular Culture: An American Lingua Franca
The “culture divide” tradition does not come from nowhere, and, as we show below, New
Age and New Con correlate with distinct neighborhoods, even if they share some
attributes. However, these “divisive” amenities are not the only ones; others may be more
commonly shared. But where to look?
One place to start is with popular culture, which almost by definition seeks to appeal to
a wide and diverse audience. We have already seen some evidence for this idea. Recall
from chapter 3 that amenities like burger joints, fast food, sports and recreation centers,
and pizza places are found in most any American zip code.
To be sure, McD’s may not embody one of Wagner’s leading motifs when he wrote of
the deep currents of a folk culture transforming a population into das Volk. But we should
not turn up our noses, all the same. Pop culture provides a set of shared reference points,
watercooler chatter, for many people who may have little else in common, not to mention
shared moments and memories of common exuberances, when the home team wins or a
song dominates the charts all summer long.
Moreover, pop culture does in fact exemplify one of the deepest currents in American
culture—the pragmatist tradition of “whatever works.” At Walmart, you can buy Jesus
candles and yoga mats; fast food restaurants have belly-busting triple cheeseburgers,
lattes, Tuscan salads, burritos, and sometimes even Korean tacos. This pragmatic tradition
of eclectic mixing, discomfort with metaphysical lines in the sand, and pluralistic border
crossing is a core American cultural tradition, even if it goes against the search in social
theory for a totalizing essence that defines a single and enduring common culture. Big
Macs, big boxes, baseball, Bond flicks, and Beyoncé—an American lingua franca.
The empirical implications for a “consensus” proposition testable with our data are
clear: pop culture amenities should be numerous, widespread, and found in many different
types of residential communities.
Martial Arts as Social Bridges
What else is broadly shared? One candidate comes from political scientist Joseph Yi’s God
and Karate on the South Side (2009), which points to Asian-style martial arts clubs. Why
martial arts? In an American context, they have become hybrid organizations whose
eclectic character appeals to many different groups.
In Asia, their Confucian values are typically associated with a hierarchical, patriarchal
past, which young, liberal reformers resist. But in America, in new soil, on a new frontier,
they are reborn, reinterpreted as a dynamic tradition open to all, including women and
racial minorities. Indeed, in his ethnographic observations of martial arts clubs on
Chicago’s South Side, Yi found diverse groups of people, where young black men
routinely and voluntarily accepted the authority of black and white women and men of
various ages, the children of Jewish professors, and vice versa.
Box 5.14 New Forms of Social Connection
Consumer researchers uncover revealing parallels between the new immigrant populations from Mexico,
Latin America, and Asia, and the Italian, Irish, or Polish 1920s communities. . . . Now as then, for instance,
ethnic grocers and ethnic media provide tangible ethnic markets. . . . In a Puerto Rican barrio in
Philadelphia . . . the “bodeguero” offers customers, along with mainstream products, an ample supply of
Hispanic goods such as plantains or vianda. . . .
. . . Hispanic customers marked their ethnicity with special products but at the same time participated in
mainstream consumerism. Clients of the Philadelphia bodegas, for instance also shopped in the
supermarket for bulk purchases. This simultaneous consumer involvement took place with media as
well. . . . My own listening to Spanish language radio confirms this mixture, with Julio Iglesias following
Madonna and Spanish-language ads for McDonald’s jostling promotion of specifically Hispanic products.
In the world of consumerism, we see once again deep and variable forms of differentiation. On the one
hand, consumers and marketers adapt mass products to particularized circuits. On the other, consumers
demand, and marketers create, special ethnic products that nevertheless remain embedded in the national
circuit. Increasingly, a new circuit forms in which special products are subsequently incorporated into
mainstream consumption as in the case of ethnic shelves in supermarkets or the spread of Mexican
restaurants. . . .
The same currency, the same consumer product can have at the same moment universal and local
meaning. . . . Why then have so many observers assumed an inescapable tension between diversity and
common values? Because looking from the top, they fail to capture the duality of representations, where we
find outward uniformity yet diversity in its local adaptation.
— Viviana Zelizer, “Multiple Markets” (1999, 202–6)
Moreover, Asian-style martial arts clubs in America combine high and popular culture.
On the basis of on aristocratic Confucian principles, American practitioners are often
asked to recite virtues, write essays, or even compose poetry as part of ascending through
the belt ranks. At the same time, martial arts are standard fare at the cineplex, from Karate
Kid to Enter the Dragon to Kung Fu Panda, and have become a regular part of the
curriculum in many park districts, YMCAs, and public schools. Moreover, they promise
the excitement associated with stars like Bruce Lee or Chuck Norris, together with the
opportunity to learn self-defense skills, flying kicks, and how to punch through boards.
They appeal both to sophisticated, educated elites (who can of course like a good fight
scene as much as anybody else) and to regular Joes and Janes who like to take in the latest
action flick on a Friday night.
Box 5.15 Christian Confucians
Because of their outsider, “nonreligious” frame, the martial arts could partner with a wide variety of social
groups, including conservative Christians, who are often portrayed as parochial and hostile to foreign
cultures. At the 1000 All-Martial Arts Tournament in Pittsburgh, one participant was Kevin (white male,
thirty-eight). From his home in nearby McKees Rocks, PA, Kevin has operated the Christian Martial Arts
Academy for fifteen years. He received two “associate” degrees from junior colleges, and worked as an
avionics foreman at U.S. Airways. . . .
Kevin has been practicing martial arts for about eighteen years, since the age of twenty. “I always
wanted to do it. The martial arts movies and the morals and everything were really close to the way I felt. I
felt that it was a good thing to start, so that’s what I did.” From his training, Kevin learned “self-discipline,
morality, being humble.”
“Respect for others, respect for myself, respect for my life . . . It has actually helped guide my focus
through life. I am always learning something new, even now, even as I train by myself. You always learn
something. So if you never learn something, you are not trying hard enough.”
— Joseph Yi, God and Karate on the Southside (2009, 136)
Beyond this, while martial arts are not Christian, they are relatively orthogonal to the
tensions between biblical Christianity and “holistic” spirituality. A major reason for this is
the specific pathway through which many martial arts entered American culture. Whereas
the strands of Yoga and other Asian imports that defined the New Age movement came to
America through New England literati and college students on a hunt for self-expression
beyond Christianity, the martial arts were brought in no small measure through the US
military, an institution warmly embraced by heartland evangelicals, black and white (cf.
Moskos and Butler 1996). US military bases in East Asia exposed soldiers to the Asian
martial arts and helped create the first generation of American practitioners (Krucoff
1999). For instance, Chuck Norris—a conservative Christian—was born in Oklahoma and
learned the Korean art of Tang Soo Do when he was stationed at Osan Air Base, South
Korea, in 1958. Martial arts are accordingly often perceived less as challenges to
traditional Christianity and more as a positive supplement, or at least as neutral.
This “middle position” of martial arts has major implications. They are not typically
treated as a part of the stifling, conformist, puritanical culture against which the
counterculture rebelled. Despite sometimes involving quasi-mystical cosmic energies (like
chi), martial arts in America (in contrast to yoga) are less often associated with strident
public debates about theological matters and culture war controversies between religious
progressives and conservatives. Nor are the martial arts bound up with the historical racial
cleavages that are so deeply intertwined with so many Christian denominations; they are
historically associated with neither whites nor nonwhites.
Still, even though martial arts organizations are non-Christian, they are far from lax.
They demand discipline, hard work, and dedication. In many schools, after each class,
students must chant lists of cardinal virtues, like loyalty to parents and country. It is
routine to find teachers asking (younger) students at belt examinations about their report
cards and whether they have cleaned their rooms. Yi reports transformational experiences
among his informants that read very much like religious conversions to a better, cleaner,
more focused way of living, and connects these changes to stronger families, especially
among African Americans, and tighter social bonds across traditional ethnic divides—
cosmopolitan ethnicity, he calls it.
Martial arts clubs, in other words, cut across numerous cultural themes. To “secular
liberals” more inclined toward self-expression and personal authenticity outside of
traditional religious organizations, martial arts promise their children an education in
social responsibility and personal self-control independent from the Judeo-Christian
establishment. And those same virtues speak to cultural conservatives looking for
bulwarks of authority and discipline in a society (ostensibly) losing its moral compass.
Similarly stressing the potential of the martial arts to establish peaceful relations among
potentially opposed groups, social theorist Donald Levine for decades taught a course at
the University of Chicago on “conflict theory and aikido,” stressing how in aikido
conflictual experience can itself become transmuted into a deeply integrating source of
social bonds. These ideas led him to found an international organization, Aiki Extensions,
dedicated to the practice of aikido as a force for global peace.
Box 5.16 Martial Arts as Moral Communities
One mother expressed frustration that the public elementary schools did not motivate and challenge their
students, like her son Christian (black male).
Chris really loves Tang Soo Do (TSD). He keeps all the old belts and broken boards at home. I think
TSD really builds character. I see a lot more discipline in Chris. If he doesn’t do something I want I
just tell him, “Don’t you want to go to TSD?” and he would do it right away. Chris likes TSD so much
that he would go to class five times a week. He would spend more time on TSD than school! . . .
There is a clear path of advancement that you see, white belt, yellow, and so forth. During testing, all
the parents and friends come out. . . .
Why don’t kids get similar excitement when they go up grade-level in school? Why don’t kids get
excited over school? . . . I wish we could transfer the qualities of martial arts school to our schools.
— Joseph Yi, God and Karate on the Southside (2009, 118)
If martial arts do bridge diverse aspects of American social and cultural life, they should
evince a broad appeal that manifests in clubs across all types of neighborhoods and differs
from the relative narrowness of New Age amenities. Hence some empirical
generalizations should follow: martial arts clubs should be more strongly correlated with
New Age amenities and New Con churches than each is with the other; martial arts clubs
should be located in racially diverse and educated neighborhoods; martial arts should be
more strongly correlated with popular culture amenities than should New Age amenities.
Where Are God, Yoga, and Karate?
Our amenities database provides a unique opportunity to investigate these hypotheses. The
main variables of interest come from the yellow pages database. Martial arts clubs are
included there as “martial arts instruction.” Our New Age index sums yoga studios,
meditation centers, and metaphysical bookstores, and our Pop Culture index sums six
items: fast food restaurants, sports bars, music stores, movie theaters, sports and recreation
facilities, and warehouse stores and superstores.37
To measure New Con churches, we summed for every US zip code the total number of
10 different types of churches: Pentecostal, Nondenominational, Bible, Apostolic,
Assembly of God, Church of Christ, Full Gospel, Seventh-day Adventist, Church of God,
and Church of the Nazarene. The 10 types are also the only homogeneously conservative
listings in the yellow pages database; by contrast, Baptist, Lutheran, Methodist, and
Presbyterian include both conservative (evangelical) and more liberal (mainline) strains.38
To illustrate the different locations of these types of amenities, we begin from
descriptive statistics and work up to multivariate analyses. We first compare the total
number and national distributions of the four types—New Con, New Age, Pop Culture,
and Martial Arts—as well as their regional distributions and intercorrelations with one
another. We then join these four indexes with census data to examine the demographic
characteristics of the zip codes in which they are most numerous. National bivariate
correlations between the indexes and racial diversity follow. Finally, we estimate multiple
regression models to give a multivariate account of the different qualities that characterize
zip codes in which New Con, New Age, Martial Arts, and Pop Culture organizations are
typically located.
Pop Culture, New Con, and Martial Arts Are More Widespread than New Age
Amenities
First consider some simple descriptive statistics, as in table 5.1. Table 5.1 shows the
national total, mean, and kurtosis for New Con, Pop Culture, New Age, and Martial Arts.
Table 5.1. New Con and Pop Culture are the most numerous and broadly
distributed organizations; New Age has the fewest organizations and most
concentrated distribution
Sum
Mean
Kurtosis
New Age
5,037
0.1
111
New Con
91,071
2.2
26
Martial Arts
16,343
0.4
31
Pop Culture
164,646
3.9
22
Note: This table shows the national sum, mean, and kurtosis for the New Con, Pop Culture, New Age, and Martial Arts
indexes. The New Con index sums Pentecostal, Nondenominational, Bible, Apostolic, Assembly of God, Church of
Christ, Full Gospel, Seventh-day Adventist, Church of God, and the Church of the Nazarene. The New Age index sums
yoga studios, meditation centers, and metaphysical bookstores. The Pop Culture index includes music stores, sports
bars, fast food restaurants, movie theaters, sports and recreation facilities, and warehouse superstores.
The picture is largely in line with our expectations. New Con and Pop Culture
organizations are the most numerous, with about 4 Pop Culture and 2 New Con listings
per zip code, and Pop Culture has the flattest national distribution. New Age amenities are
the least numerous and most concentrated (highest kurtosis). Martial arts clubs are far
more evenly and widely distributed around the country. In general, “God” and “Karate”
seem to have a broader presence nationally than New Age, with popular culture (as
expected) showing the broadest reach.
Looking at regional distributions helps to further examine where these organizations are
typically located, as in figure 5.8. Figure 5.8 shows the average number of yellow pages
listings per zip code for the four indexes in each major US region: the South, West,
Midwest, and Northeast. Pop Culture is highest in the West and lowest in the Midwest.
New Con is highest in the South and lowest in the Northeast. Martial Arts and New Age
are both highest in the West and Northeast, consistent with their status as “imports” into
the more cosmopolitan coastal regions, though Martial arts clubs have a stronger presence
than New Age amenities in the Midwest and South.
Figure 5.8
This figure shows the average number of New Con, New Age, Pop Culture, and Martial Arts amenities per zip code
across each major US region, as defined according to US census specifications.
It is also worth noting that many of the highest-scoring individual zip codes fit our
expectations about the location and reach of these types of organizations. The top New
Con zip codes are mostly in the South (e.g., Memphis; Fayetteville, North Carolina; Fort
Lauderdale) and in predominantly African American and Hispanic areas of big cities (e.g.,
Chicago’s Cottage Grove Heights, South Central Los Angeles, South Dallas); the top zip
codes for New Age amenities include college towns (Boulder, Ann Arbor) and “hippie
enclaves” (Santa Fe), as well as some hip metropolitan neighborhoods (e.g., Lincoln Park,
Chicago; Chelsea, New York). The top Martial Arts zip codes include Chelsea and
Boulder, but also downtown Atlanta (72 percent black), Honolulu (mostly Asian), and
Rancho Cucamonga (outside Los Angeles, mostly white but increasingly Asian and
Hispanic). The top three zip codes for Pop Culture span downtown Atlanta, Manhattan,
and Branson, Missouri (home of Dolly Parton’s Dixie Stampede).
These different distributions suggest that these types of amenities are differentially
correlated with one another. Table 5.2 shows that this is indeed the case. The correlations
in table 5.2 broadly fit our expectations. All the amenity types are positively correlated
with one another—even these diverse amenity types are in general often located near one
another. Yet the strengths of these correlations vary. Pop Culture and Martial Arts have the
highest average correlation with the other organizational types. New Age and New Con
have the lowest correlation of any two types, but they are not negatively correlated; the
divide is not absolute. All in all, New Age appears to have the lowest spatial overlap
(among these organizations) with American popular culture, while Martial Arts and Pop
Culture are the most likely to be present in places with both New Con and New Age.
Table 5.2. Intercorrelations of New Age, New Con, Martial Arts, and Pop Culture
Note: This table shows Pearson correlations of New Con, New Age, Pop Culture, and Martial Arts with one another. N is
all US zip codes. Darker shades indicate higher values.
Next, we examine the typical racial compositions of zip codes across the United States
with many of these local organizations. We measure racial diversity as a racial entropy
variable. We calculate racial entropy for 2000 and 1990 census data, and analyze both
1990 diversity and the difference between 1990 and 2000. Racial entropy ranges from 0 to
1, where 0 represents complete racial homogeneity, with the entire zip code population of
a single race, and 1 represents maximal diversity, with a perfectly even distribution of
individuals across the various census race categories.
Table 5.3 shows the correlations of each type of amenity with racial diversity. The main
point is that racial diversity rises with all four types of amenities, although substantially
less for New Age amenities.39 New Con churches and Pop Culture are most strongly
associated with racial diversity. Martial Arts is in the middle.40
Table 5.3. Correlations of racial diversity with New Con, Pop Culture, Martial Arts,
and New Age
Note: This table shows Pearson correlations of seven types of organizations with racial diversity (1990) and change in
racial diversity (1990–2000). N is all US zip codes. Darker shades indicate higher values.
Finally, we can get a broader and more nuanced portrait of the types of areas in which
these amenities are located by examining more variables. Figure 5.9 shows that there are
some broad similarities in where all four of these amenities are typically found: in zip
codes with more cultural employment clusters, in bigger counties, and where crime rates
and job growth are relatively high. Yet New Con and New Age again stand out. New Con
is the only one of the four more likely to be where college graduates are relatively rare and
grew by relatively small amounts in the 1990s. New Age amenities, on the other hand, are
the only ones higher in Democratic than Republican counties and in zip codes with lower
increases in the nonwhite share of the population. At the same time, New Age amenities
are the most strongly associated with college graduates, both in their levels and increases.
Martial Arts and Pop Culture by contrast are associated both with college graduates and
with relatively fast growth in nonwhite residents.
Figure 5.9
This figure shows characteristics of zip codes in which New Con, New Age, Martial Arts, and Pop Culture amenities are
most likely to be found. Bubble sizes are proportional to coefficients from negative binomial regression models. These
types of models are appropriate when the outcome is a count. All variables were standardized to have mean equal 0 and
standard deviations equal 1. N is all US zip codes.
These results illustrate distinct cultural patterns in contemporary America. They show
that the sense of a culturally divided nation does not come from nowhere. Religiously
conservative New Con churches tend to be in heavily nonwhite neighborhoods with few
college graduates; religiously progressive New Age amenities tend to be in comparatively
less racially diverse and more educated neighborhoods.41 These disparities grew through
the 1990s, and analysis of 2010 data indicates that they continued to widen (see Yi and
Silver [2015] for these more recent results). At the same time, the spatial distribution of
Pop Culture and Martial Arts highlights potential bridges for this and other societal
divides.
To be sure, these results offer insight into a specific snapshot in time, and the new
century may offer new possibilities. If New Con and New Age devotees overcome
negative stereotypes and animosities, they may extend their reach further to diverse races,
classes, and sensibilities. Many practitioners, in fact, work fervently to reach all corners of
American society. Yi has pointed to the Intervarsity Christian Fellowship, a student
evangelical organization, that boasts more than 700 college chapters and 34,870 student
members. ICF generally eschews culture war issues, such as same-sex marriage, and
promotes an active program of multiracial, social justice work that unites religious
conservatives and progressives alike (Yi, forthcoming). Concurrently, many yoga
practitioners reach out to racially diverse, economically disadvantaged populations. In
New York City, the staff and volunteers of Bent On Learning, a nonprofit organization,
teach yoga to 3,300 school children every week; other groups bring yoga to prison inmates
(Schware 2012; Hill 2010; Landau and Gross 2008).
We should not forget a key point from chapter 3. Many neighborhoods may share a single
amenity but have overall scenes that differ in many other ways. We saw this in detail with
the example of body art and piercing studios in chapter 3. The specific amenities we have
focused on here—martial arts, popular culture, evangelical churches, New Age—likely
operate in tandem with many other amenities and variables to contribute to scenes that are
welcoming or unwelcoming to different groups and individuals.
Indeed, many congregations have integrated into their services elements from popular
culture, especially where they are clearly competing with other churches and leisure
activities. For instance, the widespread use of popular songs and talented performers, the
rousing political engagement of some ministers, the wide range of cultural, political, and
social activities which are joined inside the new megachurches, the openness to using new
forms of media to reach out to new audiences—these are all frequently pointed to as
features of the more aggressively growth-oriented Pentecostalism.
Evangelical churches are not alone in desiring to connect to a wider scene. Some
Episcopal churches have women ministers and openly appeal to LGBTQ parishioners. The
Church of England divided in its debates over related lifestyle and identity issues among
its leadership as they sought to respond to the more activist evangelicals. Similarly, when
the pope went to Brazil in 2013 he encouraged citizens to raise their street demonstrations
against the national government to even higher levels. These activist efforts by the Church
of England and the pope reflect the challenges faced by traditional religious organizations
at the end of the twentieth century as they compete with multiple sacred and secular
alternatives, and the desire to reenergize traditional practices by connecting to
contemporary scenes.
But, without probing the precise historical specifics, the bigger point is that religion for
many persons from Tanzania to Thailand to the South Side of Chicago is part of a broader
suite of lifestyle issues. That is, churches are often elements of a scene. The question in
choosing which church to attend is in this way not only about primordial identity
reenactment—following the path of one’s grandparents—but also an articulation of one’s
own path and the qualities and experiences one hopes to find along it. And this is not just
an issue for young, highly educated professionals. Brazil and some African countries have
seen some of the most massive growth of Pentecostal memberships especially among their
most marginalized citizens, just as many Mexican Americans make the personal
conversion from Catholicism to evangelical Christianity, along with accompanying
changes in lifestyle and taste. Similarly the proportion of American Jews who marry
Gentiles has reached over 50 percent in recent surveys (Putnam and Campbell 2010, 156).
Other paths, as we have stressed, lead many outside the church to the dojo or the yoga
studio, raising new questions about how these practices (and their practitioners) can or
cannot be integrated into the typical scenes of Christian America.
This is not a conflict-free world. But it is one where the lines of division and
commonality are drawn in multiplex and potentially new ways. The scenes approach
sensitizes us to the wide array of overlapping elements that shift where and how people
choose to live near one another. If one only looks at data on race and income, for instance,
they seem to “explain” neighborhood differences and have sparked much public debate.42
But if one looks further, the story changes. Rich and poor; black, white, and brown;
Catholic, mainline, evangelical, and Jew; secular and spiritual; young, middle-aged, and
old; more-educated and less-educated; liberals and conservatives; men and women; square
and cool; self-expressive, glamorous, transgressive, corporate, formal, traditional, and
neighborly—these and more constitute a crosscutting matrix in which individuals can find
much they share and much they do not, myriad opportunities for combination and
recombination, bridges and boundaries, but no single ultimate cleavage that determines all
the rest across all contexts “in the final analysis.” This is a more variegated and pluralistic
picture of American society than the typical blacks and whites of dueling tribes. This is an
America in which conflict and cooperation, bonding and bridging, definition and
redefinition, joining and separating, are occurring all the time, constituting diverse
community structures that are both durable and dynamic.
While this chapter has focused on scenes and residential communities, behind many of
these discussions are questions of politics. For many observers, these differences—not
only in scenes, but also in religion, education, class, race, and all the rest—really only
matter to the extent that they translate into differences in the voting booth or at the rally.
This, of course, is why Bishop’s The Big Sort created such a stir. That Americans are
apparently sorting themselves into lifestyle communities may be interesting intellectually,
but it matters to politicians and political junkies because these communities supposedly
make a difference in electoral and movement politics.
But do they? And if so, how do these lifestyle communities compare to other variables
like religion, class, and race? That is the topic of our next chapter.
6
Scene Power
How Scenes Influence Voting, Energize New Social Movements, and
Generate Political Resources
With Christopher M. Graziul
Les Frigos is a Parisian artist collective in an abandoned rail yard of a traditional workingclass neighborhood. After occupying for decades a building formerly used to cool train
cars, the artist community in “the Fridge” became a focal point of the Paris underground
art world in the 1980s and 1990s.
Figure 6.1
Les Frigos, Paris. Photo by Jeanne Menjoulet.
The Mitterrand national government and local authorities designated the surrounding
area for one of the most ambitious redevelopment projects since Haussmann. Les Frigos
did not fit into their plans and was designated for demolition. The artist community rose
up, and after years of political struggle, they successfully prevented destruction of their
building. Further, they carved out a recognized place for their activities within the city’s
official policies as a core part of the evolving neighborhood (Sawyer 2012). Les Frigos
activists joined traditional working-class solidarity themes with new issues, like
preserving suitable sight lines from their building to the Seine. More generally, they
sought to maintain a tone for the neighborhood—an anarcho-punk, transgressive feel—as
glass and steel buildings went up around them. They fought, in other words, for a scene.
These refrigerator rebels are far from alone in linking scenes and politics. Successive
local and national governments in Seoul, Korea, worked to beautify waterfronts, create
cultural meeting points, and establish the city as a center of fashion and design, often
meeting bitter resistance on the way. Bogotá’s charismatic and flamboyant (independent)
mayor (and Green presidential candidate) Antanas Mockus sent mimes into traffic jams to
encourage civility among drivers; he had opera troupes perform in poor neighborhoods to
show that culture transcends class differences. Similarly ambitious political programs have
emerged around the world, with the character of the scene sometimes taking center stage
as a topic of political controversy and target of public policy.
These developments are part of larger transformations in many political cultures.
Classical divisions between left and right are being redefined, and the range of politically
salient issues and identities is expanding and diversifying. Thus, in the United States, a
Republican candidate, George W. Bush, ran in 2000 on a platform of “compassionate
conservatism” in which the government would have a significant role to play in improving
peoples’ lives. While in office, he expanded Medicare and instituted new social programs
such as No Child Left Behind. He left office with a government much larger than when he
started. By contrast, Democrat Barack Obama, after a large Keynesian stimulus package in
the wake of the Great Recession of 2008, reduced the number of government jobs and
purchases yet came out in support of gay marriage. Here are elements of the “third way”
or “new political culture” tradition from Bill Clinton to Tony Blair, which melds fiscal
conservatism and social liberalism.
We live in a highly complex and diverse political culture. No single factor (like
affluence or education) can explain who votes for whom or where and why some political
movements (like Les Frigos) thrive in some places but elsewhere fall flat. Left and right
have assumed many new meanings in different contexts.
Discovering origins of these new patterns is a job for which scenes analysis is well
suited. Such analysis encourages a broader view of politics—linked not only to
individuals’ wealth, education, ethnicity, and religion, but also to the full range of
meaningful experiences they reject or embrace. From tradition to transgression, our scenes
dimensions and amenities database can capture and detail specific cultural aspects of the
environment salient to national and local political scenes. To understand this landscape,
we need to bring new concepts and new data together with the tried and true methods of
political analysis.
The chapter proceeds in four major sections. The first discusses how scenes provide
resources to mobilize for politics. Scenes grow more politically salient in general with (1)
the rise of culture, (2) the rediscovery of the urbane, and (3) the new political culture. The
specific dynamics of scenes’ political potency center on what we call “buzz,” the valuable
resource that scenes can generate, which may be exchanged for other resources, such as
money or trust, used as a political weapon, a mobilizing tool, and more. The second
section illustrates how scenes and their buzz can permeate local politics by examining an
episode from Toronto local politics, where groups clashed over transforming an
abandoned streetcar repair yard into an arts and community center.
The third section compares all US zip codes, identifying the scenes where new social
movements (NSMs) thrive. NSMs arose after the 1960s to support human rights, the
environment, and social justice. Shifting from analysis of their tactics and rhetoric to the
contexts that foster NSMs, we find them strongly linked to distinct local contexts—
urbane, self-expressive scenes in dense, lower rent settings, with many nonwhite and
educated residents. Walkability is also a major NSM catalyst, as stressed by Jane Jacobs,
along with concentrations of artists. Outside these settings, despite their universalist and
cosmopolitan agendas, NSM organizations are less often present.
In the fourth section, we shift to national politics. Context is again the keynote here, as
we show how presidential voting patterns shift with their scenic context. From 1996 to
2012, Democratic votes were correlated with more urbane dimensions like transgression
and self-expression; Republican votes, with more communitarian dimensions, like
neighborliness and tradition. The strength of these correlations increased threefold in this
short period. The character of the scene became an increasingly reliable indicator of
presidential voting. Scenes also shift other political variables. For instance, high rent
counties generally vote Republican, but in more transgressive scenes they vote more
Democratic—an instance of the “Bohemian bourgeois” or “Bobo” pattern identified by
New York Times columnist David Brooks. Turning to Canada, we show how individuals’
political attitudes shift along with their surrounding scenes. Finally, we analyze financial
contributions to presidential candidates (in 2000). We construct a “Blue Blood” index of
amenities—golf clubs, yacht clubs, private tennis courts, and the like—to illustrate how
scenes track zip code contributions, even sometimes in contrast to surrounding counties
and states.
What emerges is a complex and wide-ranging account of America’s political cultural
fault lines. Joining multiple intellectual traditions while moving from case studies to
national statistics, we show how scenes are deeply embedded in our local and national
politics. And we provide tools and concepts for understanding how and why this is so.
The Rise of Culture and the Transformation of Urban Politics
In the concluding paragraphs of The Economy of Cities, Jane Jacobs left her readers with a
fanciful piece of science fiction on what she considered “one of the most pressing and
least regarded” problems facing cities:
I am not one who believes that flying saucers carry creatures from other solar systems who poke curiously into
our earthly affairs. But if such beings were to arrive, with their marvelously advanced contrivances, we may be
sure we would be agog to learn how their technology worked. The important question, however, would be
something quite different: What kinds of governments had they invented which had succeeded in keeping open
the opportunities for economic and technological development instead of closing them off? Without helpful
advice from outer space, this remains one of the most pressing and least regarded problems. (Jacobs 1970,
235)
Jacobs’s book barely touched on politics. Instead, she focused on urban economics,
arguing that (1) development in general is driven by cities more than the countryside and
(2) urban development is driven by innovation more than efficiency. She elaborated these
points in rich and detailed ways later popularized and expanded by her followers such as
Edward Glaeser and Richard Florida. But she could not even begin to imagine the
potential forms of urban politics that would foster what would later be called “creative
cities.” Such governments in her mind could only be the stuff of science fiction.
Writing in the late 1960s, Jacobs can be excused for this failure of imagination.
Contemporary urban theorists—Jacobs’s followers and others—cannot. The social world
has changed since then. Since then, participation in creative activities has increased in
general, and especially for middle- and low-status persons, with the strongest growth in
the United States, Canada, and Northern Europe (detailed in table 6.1 below). “The
creative city” concept features high on political agendas of cities worldwide. Scenes of all
sorts, as we have seen, drive local economies and channel residential patterns. The styles
of political leaders and urban governance have in some cities dramatically changed,
adding new cultural and aesthetic sensitivity to their past repertoires. In addition to the
classical conflicts around crime, clean streets, race, and class, neighborhood controversies
revolve around the right mix of amenities that captures the local “spirit” and provides the
qualitative experiences (some) citizens value. Scenes accordingly become a topic of
political contestation and a source of political authority.
Table 6.1. The rise of culture: Membership in culture-related organizations, World
Values Survey
Note: Data are from the World Values Survey. Surveys are of national samples of citizens in each country, about 1,500
per country, 3,525 in the United States. The three columns for each year show the percentage of citizens who replied that
they participated in cultural and related activities. Change is the difference in percentage from the first to last year.
Question A066: “Please look carefully at the following list of voluntary organizations and activities and say . . . which if
any do you belong to? Education, Arts, Music or Cultural Activities.” To assess measurement error due to including
education, we recomputed the results for parents and nonparents of school-age children. There were minimal differences.
Darker shades indicate higher values.
Les Frigos is a dramatic case, near legendary in certain European circles. The process,
however, is global, reaching from Paris, Berlin, and New York to Beijing, Bogotà, and
Toronto. At least three major trends are driving this global process. Each heightens the
others. Earlier chapters have touched on these trends already; reviewing and explicitly
joining them here helps highlight how they combine to bring scenes more squarely into
the political playing field.
The rise of arts and culture among citizens. Though Robert Putnam’s (2000) Bowling
Alone sparked discussion and controversy with the finding that American participation in
civic associations has declined since the 1950s, he failed to detail changes in specific types
of activities. There may be fewer bowling and Kiwanis Clubs, but other types of
belonging are in fact gaining salience. Indeed, as shown in table 6.1, there is overall
growth between 1981 and 2000 in cultural organization membership (like museums) by
citizens in 27 out of 35 countries surveyed by the World Values Survey (only 35 include
over-time data by organizational type). Growth is strongest in the Netherlands,
Scandinavia, the United States, and Canada, where membership in cultural organizations
rose over 10 percent and was much higher among younger persons. Figure 1.2 in chapter 1
illustrated the dramatic scale of this process in the particular case of Canada, with steep
rises in musical groups, dance companies, independent artists, and performing arts
establishments, along with sports facilities and clubs. Chapter 1 (figure 1.3) also showed
the steady growth of arts and entertainment as a share of the total US workforce, even
through the Great Recession of 2008. This sort of ongoing transformation suggests a
potentially major breakthrough of expressive culture and personal creativity into the
populace at large.
This “rise of the arts” is also evident in other arenas: household spending on culture, the
size of cultural industries, the growth of cultural employment, and government spending.
The movement is uneven across localities and not always linear within them yet still large
and cross-national.1
Rediscovery of the urbane. If the mid to late twentieth century was an era of
suburbanization, the early twenty-first century is rediscovering and reclaiming the
urbanity of central cities. Internationally there has been a general rise since the 1980s in
young, affluent college graduates and retirees moving into cities and especially their
downtown cores, sparking urban cultural tourism and stressing day-to-day urbanist issues
such as walking, street life, adaptive reuse, and gardening (from the Paris Plage to the
Times Square pedestrian zone to Toronto’s Evergreen Brick Works). These new urbanist
sensibilities are supported by globally oriented city governments vying for creative
residents, tourists, and financial capital (e.g., CEOs for Cities).2
Why is this “rediscovery” occurring? Urban analysts have mapped components of the
change yet not formulated a clear interpretation. Gyourko, Mayer, and Sinai (2006), for
instance, show that the rise of downtown real estate values and rent in the largest US
“superstar” cities is much faster than the national average. Analogously, Cortright and
Mayer (2001) presents data for all US metro areas on the dramatic increase of young
persons in downtowns. But these authors do not explain why; they stay close to standard
census data. Richard Florida’s interpretation stresses preferences of a creative class for
tolerant and dynamic cities. Edward Glaeser highlights increases in idea generation that
arise from dense concentrations and thick networks of skilled persons. On his account, the
rediscovery of the urbane is occurring because idea production has become more
economically significant with the decline of manufacturing and the rise of knowledge
work. Saskia Sassen suggests the importance of personal relations among global actors
who prefer downtowns, and identifies producer services and the globalization of capital as
drivers. David Harvey stresses a shift from managerialism to entrepreneurialism in local
governance caused by heightened interurban competition, leading cities to pursue
intensive development strategies often oriented less toward local service provision and
more toward cultural image and place making on the global stage (Harvey 1989; Brenner
and Theodore 2005).
In chapter 5 we discussed how the attractive power of scenes shifts for different
subpopulations. Scenes provide cues about the character of a place, which some people
find welcoming and others find alien and strange, sorting themselves accordingly.
Whatever the precise cause, however, cities themselves have been transformed in the
process. Their aesthetic and cultural characteristics have become not so much givens, “just
there,” but projects, ideals at issue for citizens and leaders alike. And this means they can
be contested.
Rise of a new political culture. This is documented by Clark and Hoffmann-Martinot
(1998), Clark (2004), and others. Forms of political activism and legitimation are
changing. Lifestyle and social issues have been rising in salience relative to party loyalty,
class, and material concerns. Fiscal conservatism is increasingly joined with social
liberalism; new forms of participation and legitimacy have emerged, driven less by classic
class and primordial group characteristics and more by other forms of political
identification and mobilization rooted in different answers to the question of what “quality
of life” means—fast cars, big houses, tight communities, personal experimentation,
natural beauty, individual freedom, amusement parks, physical fitness, open spaces, dense
walkability, big-time sports, and much more. Ramirez, Navarro, and Clark (2008) provide
a detailed review of the literature in their study of hundreds of North American and
European local governments, documenting a striking degree of support by citizens for
social and lifestyle issues as well as for new forms of political activism outside of
traditional parties.
Our present concern is not to assess the causes or nature of these processes but to
highlight their political salience. Typically, they are treated in isolation, or only two out of
three are combined.3 However, all three processes generate increasing salience for scenes
in neighborhood- and city-level decisions, coalitions, and controversies. Figure 6.2
illustrates their joint operation.
Figure 6.2
These three factors—the rise of arts and culture, the rediscovery of the urbane, and the
rise of a new political culture—join to link culture to local politics through a number of
mechanisms. The rise of culture gives generalized importance to expressive concerns
across the citizenry—what kind of a person am I? How is this expressed in film, music,
clothes, and comportment? What sorts of social audiences are in a position to appreciate
and share such expressive performances of self? The goals or functional purposes of
products are complemented by their design, their appeal to the personality and meanings
valued by consumers, as we articulated in chapter 1.
The rediscovery of the urbane joins quality of life to quality of place. This motivates
considerations about what kind of place, neighborhood, or city enables one to pursue a life
deemed worthy, interesting, beautiful, or authentic. Scenes become fixtures in the urban
landscape and more salient in decisions about where to live and work. These expressive
dynamics are enhanced by global processes including the spread of the Internet, wider
interurban competition, and increasing geographic mobility, spurring deeper searches for
meaning and identity as every city and neighborhood can be compared and evaluated
against everywhere else (Sassen 1994; Harvey 1989). Thus “cultural branding” and place
identity become increasingly crucial and contested issues among civic leaders and
ordinary citizens.
The new political culture redefines these issues of quality, culture, and place in political
terms, by emphasizing how nascent leaders and social movements champion specific
lifestyle issues and consumption concerns. New questions gain political and policy
traction, such as how to create attractive and vibrant scenes that offer amenities (parks,
music venues, bike paths, etc.) supportive of citizens’ quality of life demands; how to use
these amenities and scenes as levers for economic growth, community development, and
social welfare concerns; and how, for elected officials and movement leaders, to mobilize
citizens’ emotional allegiance to particular types of scenes for electoral advantage and
other policy goals. These three factors have combined in many cities where political and
civic leaders create a new vanguard reshaping cities in a more culturally expressive
direction (cf. Pasotti 2009; Lees 2003; N. Smith 2002). In the process, scenes become
political opportunities for ambitious leaders and objects of contestation among citizens.4
Scenes Politics as Resource Interchange, Boundary Work, and Symbolic Inflation
Management
The rise of citizen interest in the arts, combined with the aesthetics of some scenes, adds
new elements to politics. We first elaborate a new political resource we call buzz, next we
analyze buzz in a Toronto arts neighborhood, and then we consider new social movements
and their dynamics.
Classic political resources like money and votes can acquire new import in the hands of
active supporters of scenes. In assessing how and why, here as in earlier chapters, we join
scene concepts with more established processes to examine how scenes “feed into” other
domains. For instance, chapter 4 investigated links between scenes and economic growth,
and chapter 5 showed connections between scenes and residential communities. Such
“feeding in,” however, does not occur automatically, without controversy, rhetoric,
negotiation, pressure, coalition building, and authority—without, in a word, politics. In the
process, the excitement and energy projected by the scene—its buzz—becomes a valuable
resource that may affect and redefine other valuable resources, such as money, political
support, and votes.
“Buzz” refers to the symbols and signals circulating around a scene, the message that
something is happening here. Such symbols can be extremely valuable, drawing
investment, attention, visitors, migrants, and more. Yet buzz is often produced and spread
by cultural actors such as artists who have (relatively) small amounts of other resources
like money, political office, or local trust. Accordingly, as the value of buzz has generally
increased, conflicts over controlling its production, distribution, and consumption are
reshaping city politics, giving new groups access to power and creating potential
coalitions between them and older institutional actors.
One avenue through which buzz can become a source of influence is by exchanging it
for other resources. For instance, a developer is in the business of extracting economic
value from new buildings. This endeavor is not intrinsically aesthetic or cultural, but it can
be (1) enhanced if the buzz of the surrounding scene attracts attention and investment, (2)
stymied or authorized by political regulations, and (3) legitimated or delegitimated by
local residents. Here, scenic buzz, political power, and community influence are inputs
into a mainly economic process for the developer. Yet from the perspective of scene
participants, the developer’s cash and the politician’s authority may be assessed and
engaged in terms of whether they help the scene to enhance the experiences that it
cultivates—heighten its glamour, sharpen its self-expressiveness, deepen its local
authenticity, renew its ethnic authenticity. Similarly, if political support for politicians
depends on meeting citizens’ quality of life demands, and lively scenes provide quality
urban living, then buzzing scenes become key inputs for the exercise and maintenance of
political power. Further, if a scene enhances neighborhood trust (such as by providing
public venues for shared experiences), then local neighborhood leaders, who depend on
that trust to wield their influence, will depend on cultivating the artists, cultural groups,
and diverse amenities that generate the scene. At the same time, support from influential
neighborhood leaders can enhance solidarity among residents who are in turn more likely
to treat the scene’s buzz as a neighborhood asset.
Still, since scene activists (artists or otherwise), however defined, are normally small
minorities of even aesthetically minded neighborhoods, how they interface with other
political logics is essential to assess. The capacity for aesthetic talents—dramatic flair,
vivid drawing, poetic speaking, seductive music, sleek design—to enhance “normal”
political resources like money makes buzz a potent resource in its own right. The impacts
of such aesthetic talents are further enhanced as politics can potentially engage citizens via
smartphones, social media, and visual excitement to degrees unimagined just a few
decades back. If this is obvious in North American cities, it was also apparent in the Arab
Spring uprisings from 2010 onward. Even in Egypt and Syria, villages and political groups
competed over the attractiveness of their posters, slogans, and parades, as they sought to
engage ambivalent citizens.
These examples illustrate a key point from the resource approach to politics: most
citizens spend a tiny portion of their total resources on politics; there is huge “political
slack” most everywhere. Winning often means increasing turnout, even just a little bit, not
necessarily changing people’s minds. Traditional enticements are cash, patronage jobs,
Christmas chickens, and similar material incentives; but as these have been declared
immoral and corrupt resources from Chicago to China, activists have sought alternative
resources. Enter buzz. Used effectively, the emotional engagement generated by artists and
other experts in the ways of buzz encourages average citizens to spend time and money to
energize the scene and build a political base for its supporters.
Social interchange does not mean agreement. There is constant opportunity for political
struggle, coalition, and creative reinterpretation of business, aesthetic, neighborhood, and
political practice. For instance, a community leader who seeks to build trust among
neighbors through a public festival stakes her influence on the scene engaging rather than
enraging local residents’ sensibilities. Aesthetic disagreements about amenities and culture
become intertwined with disagreements about the nature of the community. Political
leaders who seek to win elections and mobilize citizen action through local cultural
policies stake their political power on the scene enriching citizens’ lives. They must
deliver the cultural goods, and failure to do so can be politically damaging. For their part,
activists who grow scenes by using buzz to attract money, political clout, and residential
community support stake the scene’s ongoing vitality on attracting wealth, power, and
local trust. They may thus face charges of co-optation, selling out, and domestication. And
conversely, amid rising rents, increasing property values, and new developments, scenes
may need to deliver some return on their buzz in the form of financial subsidies, political
backing, and residential solidarity to keep the scene solvent and anchored in terms of its
characteristic experiences and practices (shining glamorously, transgressing boldly,
expressing oneself improvisationally, etc.)
Scenes transform other political dynamics that can be thought of in resource terms.
Scene buzz may become “inflated,” decreasing its reliability as a signal of the scene’s
experiences. That is, as a scene’s buzz expands and draws more enthusiasts, more people
may display external symbols of the scene without a corresponding deep personal
commitment. This can reach a point at which possessing formerly clear symbols (T-shirts,
music tracks, certain magazines, certain interior décor) may become fuzzier indicators of a
person’s engagement in the fundamental emotions and practices that “back” the scene’s
buzz, diluting its symbolic potency and expressive energy. Inflated buzz becomes
symbolic sizzle without the emotional steak of the scene, akin to a hundred-dollar bill that
cannot buy a cup of coffee.
Similarly, the volume of buzz in circulation may be affected by its “interest rates.”
Some scenes may exhibit expansionary policies, to extend buzz far and wide with few
strings attached (as in “low commitment” pop music or club districts). Others may set high
borrowing costs and expand buzz less (as in Goth or heavy metal music, or perhaps
fraternal social clubs that require intense commitment to adopt their symbols). Low
interest rates in buzz may attract considerable investment in a scene (in monetary and
other forms), as many people may decide to give it a try. This can lead to rapid growth but
also to unsustainable inflation. High buzz interest rates may drive up the price of
participation, making the scene more exclusive (and the rent higher), as in scenes that
place limits on expansion to preserve their authenticity, via political zoning or informal
mechanisms.
Zukin’s (1989, 2010) discussions of political-economic dilemmas around the desire to
preserve authenticity of places like New York City’s Lower East Side is one recent case in
point. Authenticity politics generally become more heated in conjunction with buzz
inflation, deflation, and other substantial shifts uncoupling the more symbolic from the
material practices of the scene. The risk of being labeled “inauthentic” rises if political
leaders and others visibly change enduring and deeply embedded dimensions of a scene.
We further explore such issues for policy making in chapter 7.
More generally, many city officials have responded to the processes listed in figure 6.2
by crafting policies designed to use their local amenities and scenes as levers for bringing
tourists, new businesses, and residents. Archetypical examples are the renovated railroad
station with “authentic” stone and steel framing a chic restaurant/bar or housing
community arts groups and farmers’ markets (cf. Zukin 1989). At the same time, those
who provide key inputs into the production of a buzzing scene may threaten to withhold
their services and cut the supply and quality of buzz for a given place. These could include
artists, photographers, writers, promoters, designers, and performers, among others.
Insofar as the profitability of an area’s businesses, the social cohesion among its residents,
and the election of its politicians depend on that buzz continuing, this withdrawal could be
a major threat. If presented as such, it would become a buzz strike.5
These sorts of volatile and conflicting negotiations of key scenes resources are more
common with rapid growth, inflation, and deflation. These may lead local scenes
participants and visitors to raise doubts about the scene’s continuing solvency, and further
possible controversy or out-migration. The concern that artists and their friends are just
gentrifiers can be invoked. Some places have generated buzz inflation by encouraging
rapidly growing tourist and club districts that may come to dominate the locals; fearing
this, others have pursued “sustainable” growth in buzz, restricting restaurant and liquor
licenses to more slowly integrate an emerging scene into existing residential
neighborhoods and industrial areas. These sorts of policy decisions embedded with scenes
dynamics, we suggest, offer a critical piece of the interpretation omitted by the more
narrowly descriptive studies of rent or migration by Gyourko, Mayer, and Sinai and
Cortright and Mayer cited above.
Such interchanges, boundary work, inflationary cycles, and policy decisions create new
political opportunities and new problems for policy makers to address. Such processes
vary considerably across contexts. It can help to clarify some local cases by considering
how they link to broader propositions about scenes and the political dynamics of their
buzz.
• Where local politics is more tightly coupled with national politics, participants are more likely to support
cultural organizations and amenities capable of creating buzz that extends nationally or internationally. But
there is often a potential conflict between distant priorities and local authenticity, which scenes participants
must struggle to resolve.
• When themes like egalitarianism and anticorporatism are shared across multiple scenes, they are more
likely to grow into a broader social movement. Conversely, individual self-expression may stress uniqueness
and discourage engagement with collective political issues. Scenes that stress creative individuality can thus
conflict with the political logic of “compromise and join others on common issues.”
• Certain scene participants such as artists, writers, or media professionals with distinctive buzz-generating
resources may be sought out by others who lack these resources.
• In conflicts among residents about integrating a scene (especially a new scene) into their neighborhood, the
moral contribution of local artists’ buzz to the local community (e.g., building versus undermining trust) can
become an important political controversy. Political controversies can be mapped and negotiated in terms of
the 15 separate scenes dimensions. If new activists and others seeking compromise look for common ground
as well as areas of conflict across the 15 dimensions, they may be able to reduce the perceived public policy
distance between new and old.
• In conflicts over cultural developments’ impacts on the local scene (e.g., building a new museum), residents
may be concerned about impacts of heightened buzz on traditional and local neighborhood issues (e.g.,
traffic and home prices) while arts management professionals (curators, museum directors, etc.) may operate
from a more cosmopolitan perspective (e.g., judge local projects in reference to global icons).
• Where conflict revolves around industrial policy to subsidize local scenes, the economic consequences of
area artists’ contributions to the scene’s buzz may become central political issues.
• In a patron-client political culture, political leaders will tend to resist generic cultural planning frameworks
and instead support specific cultural clients separately to build scenes dependent on and loyal to them
personally, rather than generalized policy resources equally accessible to all. Conflict will revolve around
access to key patrons as well as movements pushing for “reform” or seeking to develop a generalized “artist
class consciousness” rather than particularistic relationships.
• When historically countercultural scenes begin to cooperate with established business interests, political
organizations, and residential groups, critiques may arise that the scene’s core values are being, respectively,
sold out, co-opted, or domesticated. Internal controversy will revolve around the scene’s capacity to deliver
its core cultural experiences and integrate new participants as it grows and becomes more interdependent
with other domains.
As the rules of the game shift across political contexts, so do the impacts of resources:
money talks in a business-dominant power structure, but votes count more in an
egalitarian system, while the arts dazzle the more aesthetically aware. Some hypothetical
examples of shifts in resource impact are listed in table 6.2 to illustrate this sort of
contextualist logic.6 For instance, it suggests that money counts highly in a businessdominant political system, while buzz is low. But in other political systems in table 6.2,
the rules change. These different “ideal” types overlap empirically, however, so that even
within the same neighborhood people may fight over whose rules and resources should
rule. This illustrates how scenes redefine legitimacy and power through transformations of
general rules into specifics.
Table 6.2. Political contexts shift the value of resources
Ideal types of political systems
Resource
types
Business
dominant
Politically
dominant
Residential
Scene
neighborhood
Egalitarian dominant dominant
Money
H
M
L
L
L
Votes
L
M
H
M
M
Community
influence
L
M
M
M
H
Political
leader access
L
H
L
L
M
Buzz
L
L
M
H
L
Note: This table illustrates how resources shift in their impact in different political contexts. It highlights resources and
contexts of the sort we stress in this paper, separating two types of power, votes and political leader access. Other
resources may be more salient in different settings. The differences in impact are due to shifting rules of the game
across different contexts. Example: as Chicago’s traditional political dominance has declined, so has the impacts of
those resources most important for a politically dominant power structure. H = high; M = medium; L = low.
In sum, scenes are targets and resources for contemporary politics. Fights over the
dimensions of the local scene—what it means to be legitimate, theatrical, or authentic,
which dimensions to cultivate here and now—may become bound up with existing
political cleavages like race, age, or class (e.g., black scenes versus white scenes, worker
scenes versus professional scenes, youth scenes versus elderly scenes). Or they may
proceed within and across such categories, generating new bedfellows and new enemies.
Whatever the specifics, however, the present point is that key dynamics of contemporary
politics can be better understood through attending to the power of scenes.
Toronto’s Wychwood Barns: A Case Study Illustrating the Contentious
Politics of Local Scenes
We offer these propositions and hypotheses to illustrate the dynamics of several
overlapping processes: resources, exchange, issue areas, inflation, buzz strikes, and so on.
Many more theories could be formulated and the ones we have listed could be empirically
tested. Our main concern here, however, is to suggest that the politics of scenes can be
analyzed with concepts that are no more evanescent or intractable than traditional local
politics issues like zoning and tax rates. The case of Toronto’s Wychwood Barns and
neighborhood controversies over its buzz feature issues found globally in local conflicts
involving the arts. The case illustrates how the politics of lifestyle issues in neighborhood
scenes can be just as contentious as fights over money or power. And it shows how these
various resources can join and do battle.7
The Wychwood Barns are former Toronto Transit Commission (TTC) streetcar repair
barns. They were built in the early twentieth century near Wychwood Park, an artist
colony with an Arts and Crafts aesthetic of the pristine natural landscape (Berland and
Hanke 2002). By the mid-1990s, the Barns were a barely used symbol of industrial age
rust in the midst of a dense, now Midtown, residential community.
In the 2000s, what to do with the empty barns became a hotly debated issue as the
surrounding neighborhood changed. Amalgamating Toronto with its suburbs had left two
incumbent councilors vying for one position. Local political leaders in turn became the
symbolic focus of questions about what kind of community the newly created ward would
be.
Thus, the victorious Joe Mihevc—a PhD in theology and social ethics, able to casually
quote Freud and Jane Jacobs and recite the history of various parks movements—attracted
both intense scorn and praise, with opponents chanting “Heil Mihevc” at community
meetings and supporters referring to his “Zen-like calm” (Landsberg 2002). Local political
leadership became key in the ensuing dispute over the Barns, as Mihevc became a major
force in the movement to transform them into a cultural community center. The critical
resource question for advocates of turning the Barns into an arts hub concerned presenting
their case so as to mobilize citizens and civic leaders to back the project. One answer was
to broaden the “arts” beyond private production and passive spectatorship to include
shared consumption and active participation by citizens in festivals, art classes,
community gardening, farmers’ markets, and more—into a distinctive scene. At the same
time, the task was to frame the project in a manner that appealed to family- and
community-minded locals.
Underlying the allure of the Barns as a vehicle for buzz creation and circulation were
changes in the numbers and types of local residents. Housing values were steeply rising,
new residents with young children were moving into the neighborhood, development
pressure was increasing, and there were rising percentages of residents reporting “multiple
ethnic origins,” working in arts, culture, and recreation, working from home, and walking
to work. “Who are we?” was floating in the air.8 While traditional residential and
ethnocultural bases of identity and community were in doubt or flux, an arts-oriented,
expressive, urbanist, industrial heritage transformation project was ideally situated as an
attractive experiment in new forms of community. This proposal stood in stark contrast to
the quiet Arts and Crafts colony of its past. “What kind of park do we want?” became a
proxy for “what is the nature of our community?” Without any clear or universally shared
answer, these questions grew politically divisive.
What lit the fuse was the question, what is a park? Both Mihevc and his opponent
campaigned for the car barns to become “100% Park,” which at the time meant “not
commercial real estate development.” But when it came time to specify what “100% park”
meant, the community split. Artscape—an organization that rehabilitates (and eventually
would develop) buildings into arts hubs—had been attending community meetings and,
together with Mihevc, began to formulate plans to adaptively reuse rather than demolish
some or all of the old buildings. They would house arts groups and farmers’ markets,
community nonprofits and community food centers. Local ecologists and natural
preservationist groups proposed returning the area to its original natural state.
All these alternatives were plausible “parks.” Which option to pursue became the focal
point of heated community meetings as residents debated the sort of scene they wanted to
live near. Some residents dubbed themselves Neighbours for 100% Park and started
advocating for traditional grass, trees, playground, and sports fields. Others, some tapped
by Mihevc, calling themselves Friends of a New Park, organized support for considering
multiple uses in general and the Artscape proposals in particular.
The formation of these small, ad hoc organizations creates publically visible organized
groups that are at least symbolically collective and represent more than private selfinterests. They can join neighbors and claim volunteer time, money, and media attention
more easily than a set of individuals, thereby decreasing “resource slack.” They become
new mobilizing platforms, which often emerge as political conflicts mount and more
participants turn out for meetings, fund-raisers, and more.
The Barns thus became the central occasion for debate and collective mobilization
around the type of scene appropriate for the community. Run-down and boarded-up, they
symbolized the dirty work and noisy, mechanical intrusion onto what had been a pastoral
scene. Turning them into grass, trees, and a children’s play area was for some citizens a
welcome way to end that era, to kick the manufacturing age into the dustbin of history.
“Artists need space to work, I understand that,” said a leader of Neighbours for 100%
Park, film producer, and Wychwood Park resident, “but one of the things that makes city
life bearable to me is a park” (Conlogue 2002).
The Artscape proposal, supported by Mihevc and Friends of a New Park, proposed an
alternative, treating the industrial past as part of a collective learning process. “The Green
Barn will be the meeting place of culture and nature. . . . The community can explore
nature while framed by the historical architecture and heritage of the TTC car barns”
(Friends 2010). Yes, humans had harmed nature, but we can now work with her rather
than on her while attempting to make work fulfilling rather than alienating—ideals that
might, they proposed, be promoted by videos of aboriginal ritual dances and realized in
food education centers, farmers’ markets, and self-expressing postindustrial artists
working within an industrial heritage building, surrounded by photographs of streetcar
mechanics.
The potential impact of this emerging scene on community solidarity was also
controversial. Friends of a New Park proposed a conception of community based not on
privacy but on publicity, interaction, and personal self-expression. The Barns would create
a “dynamic and flexible” space for a community whose identity was in flux. “A key aspect
of any sustainable project is that it be adaptable and flexible to changing conditions”
(Friends 2010). Neighbours for 100% Park, by contrast, had a vision defined primarily by
residence; the park was for those who lived nearby, an extension of their backyards. They
brought bags of lard to community meetings to graphically show all the fat their kids
would fail to burn without ample space. The buzz generated by artists living and working
in the park would bring nonresidents and set up a rhetorical division between the
cultivated and the uncouth. The Artscape proposal would create an “exclusive space where
artists can interface with thespians and activists. Neighbours may intrude if they dare”
(Neighbours 2010). The result would be the “Habourfronting” of the neighborhood. That
is, the neighborhood would be transformed into a tourist destination, where “the various
venues, gallery openings, theatre performances, non-profit activism, food depot
transactions & dare we whisper it, the prospect of booze cans . . . promise . . . a very busy
venue, hardly in keeping with the quiet residential character of the neighbourhood” (ibid.).
A beacon for outsiders and unknowns, the new scene, according to this view, would be
less a space for diverse openness and more the occasion for new divisions supported by
government largesse: “Can we spell taxpayer subsidised: G-A-T-E-D C-O-M-M-U-N-I-TY” (ibid.). These competing visions gave “whose rules rule?” political urgency.
If Friends of a New Park were “dreamy” buzz inflators to their critics, Neighbours for
100% Park erred toward buzz deflation. Neighbours for 100% Park were largely
anonymous, rarely granted interviews, and mostly presented themselves as defending
private goods rather than building public space. Perhaps the most important media
moment for Neighbours for 100% Park was when one member was reported as saying
“she doesn’t want anything new to be built nearby because guests at her friend’s dinner
party won’t have any place to park” (Barber 2002). Neighbours for 100% Park were
framed as fearful of change and outsiders, defending private turf and semiprivate goods.
Friends of a New Park, by contrast, were able to reverse the image of artists as outsiders
and deviant elites, while reframing them as upstanding neighbors and public goods. To do
so, they used their skills to build professional-looking websites with a clean design, took
residents on inspirational walks around the Barns, distributed posters, and held
participatory design discussions. They even produced a video connecting the future of the
Barns to urban problems writ large (blight, lack of public services), conjuring the history
and beauty of the structure (comparing the internal lighting to a cathedral’s), stressing
their group’s diverse base of supporters (artists, teachers, performers, environmentalists,
landscape designers, urban agriculturalists, and more), and offering images of the sorts of
activities (singing, dancing, learning) that would make the Barns exist not only for
“pastimes” but for “creating time,” not a passive park but an occasion for a “higher caliber
of existence.”
To build local trust, Friends of a New Park sought support from key civic groups. They
gathered dozens of letters of support from local school principals. Their website included
hundreds of names of local residents, with addresses proudly displayed. They publically
argued that a buzzing scene could build community just as well as grass and trees could.
More activity would mean more “eyes on the street” and a safer environment. Far from
bringing deviants and hedonists into the area, resident artists would provide theater
classes, painting classes, and more. They asserted in their video, moreover, that the arts
add value that money alone could not. “What makes a city great is not the stockbrokers.
We need the money, but we need the art more.” These efforts linked the potential buzz
from the scenes that would grow up around the artistic use of the Barns to more open and
diverse policies that credited the concerns of a traditional residential community, like trust,
safety, and schools, while asserting the independent value of active aesthetic participation
in a scene.
In the end, the promise of added buzz and its skillful deployment by activists yielded
tangible results.9 Dubbed the Artscape Wychwood Barns, the dilapidated repair yards
were rehabilitated, at a price tag of around 20 million Canadian dollars, with funds coming
from a variety of sources such as development fees for nearby condominium proposals,
provincial and federal grants for subsidized low-income housing (on the novel proposition
that below-rent artist space could be eligible for such funds), foundation and private
donations, and loans backed by the city, not to mention tax exemptions. They now house
several artists and arts groups, various music education programs, a children’s theater,
environmental organizations, a community food organization dedicated to social justice,
an ongoing slate of festivals and events, and much more. At the year-round weekly
farmers’ market, Mihevc is a regular, shaking hands and greeting voters. If the prospect of
this sort of scene was able to mobilize resources and forge coalitions, its buzzing reality
now feeds into new development, artistic creation, ongoing community gatherings, local
business, and political allegiance to the leaders able to take credit for them.
Scenes and New Social Movements
The work of the Wychwood Barns and Les Frigos activists points toward an important,
and potentially generalizable, insight implicit in our contextualist approach to politics: that
there is an affinity between (1) certain types of political organizations (e.g., environmental
groups, social justice advocates, human rights champions) and (2) certain sorts of scenes
(e.g., those that support values such as creativity, experimentation, and cosmopolitanism).
The success of the first, often termed new social movements (NSMs), may thus depend on
their location amid the second.
A brief sketch of the rise of the NSMs suggests not only a general linkage between their
politics and their aesthetics, but some specific propositions about the scenes where NSMs
should thrive. Testing these propositions using our scenes measures and national
comparative data allows us to go beyond the particularities of one or two cases and ask
what factors in general favor NSM organizations. This broader analysis gives a window
onto how scenes structure the local political landscape, and illustrates the more general
sort of contribution that scenes data and concepts can make to understanding the sources
of political activism.
The NSMs sought a new relationship to nature, to one’s body, to the opposite sex, to
work, and to consumption.10 In so doing, consumption and lifestyle issues were joined
with the classic production and workplace concerns championed by unions and parties
dominating much of politics in Western Europe and the United States over the twentieth
century. Yet even in the 1940s, some political analysts (such as Paul Lazarsfeld)
commented that American politics was more like a conversation about what clothes to buy
or what music to listen to than obeying a military commander or union boss.11 Lazarsfeld
saw these aspects of politics clearly after migrating to the United States from Austria, but
this insight later led to a new framing of politics; it was a big step toward scenes.
These new civic groups stressed new agendas—ecology, feminism, peace, gay rights—
that the older political parties ignored. Over time, other, more humanistic and aesthetic
concerns also arose: suburban sprawl, sports stadiums, urban gardening, museums,
walkability, and more. In Europe, the state and political parties were the hierarchical
“Establishment” opposed by the NSMs. In the United States, local business and political
elites were more often the target.12 Many governments were seen as closed to these citizen
activists. For instance, in the 1970s in Italy, even Communist and Socialist parties rejected
NSM concerns.
Establishment opposition of this sort encouraged the organization of NSMs and
(especially in the founding years) their confrontational tactics. But as some political
parties and governments embraced the new social issues, the political opportunity space in
which NSMs were operating drastically shifted. Movement leaders then broke from
“urban guerrilla warfare” and began participating in elections, lobbying, and advising
governments. As their issues were incorporated into the political system, their demands
moderated. Yet they added a heightened sensitivity to the emotional, musical, imagedriven, and theatrical aspects of political life.13
In a clearly related shift, business actors such as real estate developers and political
leaders and candidates often grew more green and artistic. Some refashioned concepts like
loft living or self-expression into their rhetoric and policies. National political candidates
like Bill Clinton made public appearances in sunglasses, playing the saxophone. In
addition to the traditional ethnic music events, Chicago’s Mayor Daley II added alternative
and indie music festivals to the city’s calendar. He also marched in a gay rights parade and
started turning up at art galleries.
The NSMs, in other words, reshuffled the traditional relationships between class and
politics. Their cosmopolitan concerns were too general to fit in any “workers’ party.”
Their issue specificity was too particular to focalize an entire social class. And with many
activists and supporters from educated backgrounds destined for professional occupations,
unions became less potent vehicles for transforming class differences into political
activism. Not only a new left but a more general new political culture emerged, in which
the traditional alignment of left and right to social and fiscal liberalism began to bend.14
The influence of NSMs has been so strong that what began in the 1960s and 1970s as a
radical fringe has often become mainstream. Much research on new social movements
focuses on the “successful” cases, where groups are able to effectively organize and
sometimes stage dramatic victories. We ourselves do this kind of research, as it permits
observations of new types of tactics, rhetoric, and organization at work and the assessment
of how these do or do not join with existing channels of influence.
The cost of this approach, however, is that one has difficulties determining where and
why the single or few successful cases differ from the many others, where either no
movements form or those that do are weak. The NSM rhetoric is often universalistic,
concerned with issues like environmental degradation, human rights, personal expression,
and social justice. These apply to all human beings, wherever they happen to live and
whatever their background. However, these universalistic themes do not resonate
universally, and they issue in significantly different styles of organization and political
efficacy.
Where and why do local patterns differ? Some analysts began to stress contextual
characteristics, like the local political “opportunity structure” (McAdam, McCarthy and
Zald 1996). “Framing” and “organization” were also featured as key variables affecting
the likelihood a social movement would flourish.
The specificity of universalism. A less abstract way to add to this focus on the context
for NSM success is to lay out some characteristics of the places where they first became
energized and grew. Linking scenes and social movements explicitly, Darcy Leach and
Sebastian Haunss (2009) have shown how important geographic concentrations of bars,
clubs, films, concerts, and parties were in energizing Germany’s “autonomous”
movement. Building on the cases of Hamburg and Berlin, they develop a series of
propositions about how scenes can support active movements, and how the two—scene
and movement—can create tension with each other.
In the American context, the dense, high-crime, multiethnic urban centers were the key
scenes of NSM activism. Here, young college graduates, artists, and intellectuals moved
into ethnically diverse inner-city neighborhoods. In such places, the underinvestment and
degradation of many cities was greatest, and the “white flight” to the suburbs by older and
more culturally conservative persons was often most rapid. A vision of an alternative
future emerged among (some of) those “left behind”: more humane, more sensitive to the
consequences of human actions upon Mother Nature, able to see the beauty not only in
symmetry and regularity but also in discord and disorder. Richard Sennett’s (1970) The
Uses of Disorder conveys some of this general attitude.
Density alone is not enough to capture what was distinctive about these NSM
incubators. To see why, consider Jane Jacobs. Her Death and Life of Great American
Cities ([1961] 1992) became a call to arms for urban reformers internationally. Her ideas
were inspired and refined in no small part by her experiences as an activist, struggling
against urban renewal projects from the likes of Robert Moses in New York City and Fred
Gardiner in Toronto, the two cities in which she spent much of her life. Moses and
Gardiner proposed building huge freeways to give suburban residents quick and easy
access to downtown businesses and amenities. These would cut through existing
neighborhoods and, Jacobs and her followers argued, destroy what made them work.
Particularly important was their walkability. People out on the streets, she argued, are
more likely to bump into one another, encounter others different from themselves, avoid
getting stuck in stultifying routines, and keep their eyes out for criminal activity. Car
culture threatened the very basis of urban community, and with it the spirit of
cosmopolitan diversity crucial to the progressive new social movements.
Box 6.1
What one should learn from artists. What means have we for making things beautiful, attractive, and
desirable, when they are not so? and I suppose they are never so in themselves! We have here something to
learn from physicians, when, for example, they dilute what is bitter, or put wine and sugar into their
mixing-bowl; but we have still more to learn from artists, who in fact, are continually concerned in
devising such inventions and artifices. To withdraw from things until one no longer sees much of them,
until one has even to see things into them, in order to see them at all—or to view them from the side, and as
in a frame—or to place them so that they partly disguise themselves and only permit of perspective views
—or to look at them through colored glasses, or in the light of the sunset—or to furnish them with a surface
or skin which is not fully transparent: we should learn all this from artists, and moreover be wiser than they.
For this fine power of theirs usually ceases with them where art ceases and life begins; we, however, want
to be the poets of our lives, and first of all in the smallest and most commonplace matters.
— Friedrich Nietzsche, The Gay Science (2001, bk. 4, aphorism 299)
Just as important as walking were the arts. Artists themselves were of course often
politically aligned with the NSM agenda, and they did tend to live in the sorts of
neighborhoods Jacobs and others were fighting to protect and extend. But their
significance goes deeper. The artist himself could be a catalyst for urban change and the
agent of a new vision for what an urban neighborhood could be. Not only a scene of
depravity, despair, and dirt, the city itself could become a source of beauty, an aesthetic
phenomenon.
The artist, in other words, would be a vehicle for turning inner-city filth into a space for
cultivating the self, a source of expression rather than anxiety. Aesthetic experience itself,
that deepest and most humane of qualities, could be a human right, and the new social
movements would have to create a space for all persons to develop those qualities in
themselves. And insofar as this aspiration went against the types of culture and the vision
of society favored by the organs of the state and the corporation, it would naturally tend to
take on a more transgressive, countercultural flavor. A different world was in the making
in avant-garde paintings and poetry, and it would of course be hard for the people
benefiting from the current system to accept what was to come.
Box 6.2 Adam Smith on Urban Cultural Policy
A man of low condition . . . is far from being a distinguished member of any great society. While he
remains in a country village his conduct may be attended to, and he may be obliged to attend to it
himself. . . . But as soon as he comes into a great city, he is sunk in obscurity and darkness. His conduct is
observed and attended to by nobody, and he is therefore very likely to neglect it himself, and to abandon
himself to every sort of low profligacy and vice. . . . There are two easy and effectual remedies. . . . The
second of those remedies is the frequency and gaiety of public diversions. The state, by encouraging, that
is, by giving entire liberty to all those who for their own interest would attempt, without scandal or
indecency, to amuse and divert the people by painting, poetry, music, dancing; by all sorts of dramatic
representations and exhibitions would easily dissipate, in the greater part of them, that melancholy and
gloomy humor which is almost always the nurse of popular superstition and enthusiasms. Public diversions
have always been the objects of dread and hatred, to all the fanatical promoters of those popular frenzies.
— Adam Smith, The Wealth of Nations (1776, bk. 5, ch. 1)
It was in the wake of these experiences, well before the current vogue of treating artists
as urban development agents, that some of the first and most visionary urban cultural
documents were formulated. And these documents carried forward themes going even
further back, all the way to the first stirrings of European urbanization, as the selection
from The Wealth of Nations in box 6.2 illustrates.
New Social Movements Are Typically Located in Dense, Walkable Areas with SelfExpressive Scenes and Many Artists
We can take these general observations and translate them into testable empirical claims.
NSMs should thrive in dense, diverse, places where high crime coexists with college
graduates and artists. They should be in urbane, self-expressive, and transgressive scenes.
And NSMs should be strong where more people spend more time walking. To take on
these issues empirically, we made an NSM index, which sums for every US zip code
human rights groups, environmental groups, and social advocacy groups.
Table 6.3 lists the 30 zip codes with the most NSM organizations in the country (as of
2000). Naturally, many state capital and Washington, DC, neighborhoods are at the top of
the charts. But it also suggests that NSM activity is driven by more than access and
proximity to political leaders. The San Francisco Bay Area, for example, has five of the
top 30, with zip codes of the Mission and Tenderloin districts having the highest totals.
Portland’s historic Goosehollow, whose neighborhood association explicitly places
walkability, parks, and cultural opportunities among its main goals (Goosehollow.org
2015), and Seattle’s dense, hip Belltown have the most NSM organizations in Oregon and
Washington.
Table 6.3. Top 30 new social movement zip codes, nationally
Zip code
Place-name
NSMs
Zip code
Place-name
NSMs
20036
Washington, DC
109
60604
Chicago, IL
24
20005
Washington, DC
82
10022
New York, NY
23
20006
Washington, DC
53
22314
Alexandria, VA
23
20009
Washington, DC
49
98101
Seattle, WA
22
94103
San Francisco, CA
47
02108
Boston, MA
22
20002
Washington, DC
44
19107
Philadelphia, PA
20
95814
Sacramento, CA
37
03301
Concord, NH
20
53703
Madison, WI
32
97205
Portland, OR
20
10017
New York, NY
31
94105
San Francisco, CA
20
20001
Washington, DC
29
32301
Tallahassee, FL
19
94612
Oakland, CA
28
02116
Boston, MA
19
10001
New York, NY
27
94129
San Francisco, CA
19
10016
New York, NY
26
94102
San Francisco, CA
18
55104
Saint Paul, MN
25
10021
New York, NY
18
43215
Columbus, OH
25
48933
Lansing, MI
18
Note: This table shows the zip codes with the most new social movement organizations nationally. The NSM index
includes human rights groups, environmental groups, and social advocacy groups.
Figure 6.3 moves beyond these few dozen zip codes and evaluates the variables
typically associated with NSM organizations nationally. Because most zip codes have no
NSMs, we divide all US zip codes into two categories: those without NSMs and those
with at least one NSM. We then ask two related but distinct questions: (1) What conditions
are associated with the presence of any NSMs? And (2) given the presence of at least one
NSM, what conditions are associated with the presence of many or few NSMs? The left
column addresses the first question while the right column addresses the second.
Figure 6.3
This figure depicts results from what is called a hurdle model. These models are used in situations where the outcome is
relatively rare but can take on multiple values (e.g., major sports teams in US counties). The purpose is to
simultaneously learn something about the conditions that give rise to the presence of any NSMs and the conditions that
give rise to more NSMs (e.g., any major sports teams versus five major sports teams in Chicago’s Cook County). It is
not immediately clear that the same factors come into play, as our results show. Note that, due to how a hurdle model is
estimated, the two columns represent two distinct submodels whose bubble sizes cannot be compared across each
independent variable but can be compared within each model. Variables have been standardized to have mean equal 0
and standard deviation equal 1 at their respective levels of analysis (zip code or county). Unless otherwise noted, nonscenes variables represent zip code–level values for 1990. Cultural employment clusters and other scenes variables are
identical to those used in previous chapters. N is all US zip codes. More on variables and methods of analysis is in
chapter 8 and the online appendix (press.uchicago.edu/sites/scenescapes).
Where do NSMs thrive? They are usually present in high rent, high crime counties, and
there are more of them in Democratic counties. Neighborhoods with any (and many)
NSMs are usually in dense, lower rent zip codes with strong cultural employment
concentrations, nonwhite residents, and college graduates. Moreover, walking, as Jacobs’s
ideas would lead us to expect, is a crucially important element of an NSM-friendly scene.
But cultivating an openness to personal expression and a general feeling of Urbanity is
important as well. Our (YP) self-expression and Urbanity measures are both strongly
linked with NSM presence. Urbanity in particular is linked with not only the presence of
any NSMs but also many of them.
The left graphic in figure 6.4 shows, all other things equal, a moderately positive
relationship between our Urbanity factor score and any NSM presence. In our model, there
is a roughly 15 percent chance that there are any NSMs in the most Urbane scenes. The
right graphic shows that, however, among the zip codes with at least one NSM, there are
likely to be dramatically more NSMs where the sense of Urbanity is strong. Less Urbane
scenes tend to have only a few NSMs (the model predicts under 2 per 1,000 amenities);
average Urbane scenes have a handful (about 5 predicted per 1,000 amenities); while the
most Urbane scenes have many more (18 predicted per 1,000 amenities). Urbanity, in
other words, while important in NSM formation, seems to be a key driver of NSM
expansion beyond our other standard variables.15
Figure 6.4
This figure shows the marginal effects of Urbanity on new social movement organizations. The figure is read left to
right, where the y-axis indicates the predicted probability of having any NSMs and the predicted total number of NSMs
(given that any exist) for an average US zip code (defined using the covariates listed in figure 6.3), respectively. The xaxis indicates an increase in the average Urbanity of the zip code from very low (highly Communitarian) to very high
(highly Urbane).
Box 6.3 The Ambivalent Attitude of Bohemia toward Political Activism
One expression of the prevailing disillusionment was the abandonment of politics in favour of morbid
introspection, embellished by all the gothic horror trappings of romanticism, with its skulls and moonlit
graveyards, medieval castles and wild landscapes, and indebted to the poetry of Byron. . . .
Later generations of bohemians maintained a tradition of political intransigence. Yet their utopian
idealism was liable to sour into gloom or cynicism, for their revolutions always failed, or, even worse, if
successful were betrayed. In this as in other ways the opposition between bohemian and bourgeois masked
a certain similarity, since revolutionary absolutism not infrequently ended in apolitical indifference.
— Elizabeth Wilson, Bohemians (2000, 23–24)
Self-expressive, urbane, walkable, dense, diverse, low rent neighborhoods—these are
indeed places that very much resemble Jane Jacobs’s Greenwich Village and Annex
neighborhoods. Where these factors conjoin, they create an experience that is apparently
conducive to NSM activity; elsewhere, such activity is more rare.
The Ambiguity of Transgression
One somewhat unexpected result in figure 6.3 concerns transgression. The degree to
which a place has amenities that support a spirit of transgression is unrelated to whether it
is home to new social movement organizations. This is the case whether we are talking
about places with any NSMs or those with many NSMs.
This may seem surprising if we think of “transgression” in the revolutionary sense. But
it is consistent with a strong tension within historically Bohemian culture. On the one side,
there is the activist strand, which says that rejecting the present world also means
reforming it economically and politically. But there has always been another side of
Bohemia, one more suspicious of political activism.
This less activist strand is more concerned with transgressing norms of style and
culture. Bohemians of this variety tend to retreat from public political engagement rather
than attempting to overturn the existing order, much to the chagrin of anticapitalists,
including Marx himself. And even when this element becomes political, it does so in a
more aesthetic way. For instance, when Baudelaire commented on his participation in the
1848 revolutions, he said he did so for the rush of tearing something down and being
carried away by a passion larger than himself—not to spread the rights of man. Moreover,
he could and did find similar experiences in the oldest of Old Regime institutions, the
Catholic Church. While it is of course only circumstantial, and we should not overinterpret
a finding of statistical insignificance, this result may suggest indirect evidence of the
persistence of this political ambivalence built into antiestablishment culture.16
Self-Expressive Scenes Heighten the Political Salience of Walkability
Figure 6.5 shows that walkability is one of the most widespread characteristics of
neighborhoods in which NSMs are located. Zip codes whose walkability is high (i.e., one
standard deviation higher than average) have in our model about 60 percent more NSMs
than zip codes with average walkability, when controlling for our other variables.
Ambulatory experience may indeed create a natural sensitivity to classic NSM issues like
zoning, the environment, diversity, urban planning, and aesthetics.
The above analysis, however, treats walkability and the scenic features of the
neighborhood (like self-expression) independently, asking how much an increase of one is
associated with an increase of NSMs net of changes in the other. But, of course, they do
not operate independently. One of the main aspects of movements from Jacobs on was that
they should not: the urban experience itself should become an uplifting opportunity, and
that means taking the time to wander through it and listen to what it says. This ethos
suggests a tractable hypothesis: where this conjunction of walking and self-expression
occurs, we should be more likely to find those organizations dedicated to preserving and
expanding the vision of life it suggests: cosmopolitan, open, ready to learn from the
experiences of chance encounters and diverse others, out to make the world more beautiful
and sustainable than it currently is. That is, it is in those places where walking and selfexpression come together that we would expect some of the largest current concentrations
of NSM activity to be found.
Figure 6.5 shows how important this interplay between walking and self-expression can
be in fostering new social movement political activity by exploring how varying each
affects their joint relationship to NSMs. The left graphic shows again that, ceteris paribus,
more-walkable places are in general more likely to have any NSMs than less-walkable
places are. But it also shows that this difference is greater in more self-expressive scenes:
in the country’s least self-expressive zip codes, the most walkable places have about an 8
percent higher predicted probability of having some NSMs than the least walkable places
do. But in the country’s most self-expressive scenes, the most walkable zip codes exhibit a
13 percent higher predicted probability of having at least one NSM than do the least
walkable zip codes.
Figure 6.5
This figure shows how walkability and self-expression interact to predict greater numbers of NSMs. The figure is read
left to right, where the y-axis indicates the predicted probability of having any NSMs and the predicted number of NSMs
(given that any exist) for an average US zip code (defined using the covariates listed in figure 6.3), respectively. The xaxis indicates an increase in the average (YP) self-expressive scene within each zip code from very low to very high.
Box 6.4
A city street equipped to handle strangers, and to make a safety asset, in itself, out of the presence of
strangers, as the streets of successful city neighborhoods must always do, must have three main qualities:
First, there must be a clear demarcation between what is public space and what is private space. Public
and private spaces cannot ooze into each other as they do typically in suburban settings.
Second, there must be eyes upon the street, eyes belonging to those we might call the natural proprietors
of the street. The buildings on a street equipped to handle strangers and to insure the safety of both
residents and strangers, must be oriented to the street. They cannot turn their backs or blank side on it and
leave it blind.
And third, the sidewalk must have users on it fairly continuously, both to add to the number of effective
eyes on the street and to induce the people in buildings along the street to watch the sidewalks in sufficient
numbers. Nobody enjoys sitting on a stoop or looking out a window at an empty street.
— Jane Jacobs, The Death and Life of Great American Cities ([1961] 1992, 35)
In the right graphic, we can see that the “walkability premium” for not only any but for
many NSMs is much greater in more self-expressive scenes. The difference between
walkable/less walkable increases dramatically in highly self-expressive scenes. In less
self-expressive scenes, a highly walkable zip code has on average about 4 more NSMs per
1,000 amenities than a less walkable zip code. But in the most self-expressive zip codes, a
more walkable zip code has on average about 20 more NSMs per 1,000 amenities than a
low walkability zip code.
That is, when walking and self-expression come together, the result is quite likely to be
organizations advocating for human rights, social justice, and the environment.17 The one
supports the other, as Jacobs held. A neighborhood with people walking about is one with
an audience, one that holds opportunities to see and be seen. A scene that prizes selfexpression is one that legitimizes efforts to put one’s ideas, insights, and imagination
forward before others as an opportunity for experience and interaction. These sorts of
places where public sociability and personal self-expression push each other to higher
levels seem to cultivate the environments in which the new social movements have found
energy, inspiration, members, and supporters most in tune with their aims and ambitions.
These analyses thus show just how much new social movement organizations depend
on the specific character of the situations in which they work. However universal and
cosmopolitan the content of NSM goals, they appear to get much of their energy and
support from the qualities that inhere in concrete local contexts. Such qualities animate a
distinct style of life, give it urgency and importance, but they are not found everywhere or
even in many places. Dense, walkable, self-expressive, urbane, diverse, intellectual—
while each of these characteristics is important separately, when they come together they
provide powerful catalysts for new social movement activism to grow. But where they are
weak or absent, NSM styles and goals may seem alien and unwelcome, and they may face
difficulties in taking root. Jacobs-esque settings, that is, provide critical cultural meaning
and emotional energy to the more abstract environmental characteristics more often
featured in the NSM literature’s trinity of opportunity structure, framing, and organization.
Beyond these specifics, the general point again is that certain forms of politics thrive in
certain scenes but fall flat elsewhere.
Scenes and National Politics
Scenes can set the stage in which new social movement groups thrive, and define the
terms in which local political controversies are engaged. But the links between scenes and
politics clearly go beyond small organizations and neighborhood politics, to national party
identifications, and to more general political ideologies of left and right. A simple insight
as new as Aristotle, Montesquieu, Tocqueville, and Hegel tells us why this should be so:
distinct morals, manners, and habits bring with them distinct sets of political ideas; as the
former vary, so should the latter. As scenes manifest and crystallize different visions of the
good life across localities—embedded in and affirmed by their day-to-day practices and
amenities—differences in scenes should correspond to differences in their overall political
orientations. A candidate, party, or policy proposal resonates in some scenes that embody
some shared visions or values and falls flat in others.
As simple as it is, this general idea may not seem so visible in current political analyses,
which tend to treat voters in isolation from their social contexts. Still if one considers
major trends in postwar political science, some point toward a potential convergence with
scenes concepts and analysis.
Politics is not an island. Professional political analysis has shifted away from a
relatively narrow focus on constitutional and legal structures and the process of
legislation. It now situates politics within a broader context. Only after World War II did
many US academic departments of “public law” and “government” adopt the name
“political science.” The change in names marked a shift to incorporate the social and
cultural environment, in the work of authors like Gabriel Almond, Seymour Martin Lipset,
Philip Converse, and David Easton.
Another challenge to the field was the penetration of ideas from economics, as “public”
or “rational choice” models entered political science after the 1970s. While the public
choice tradition had a strong individualistic cast, the processes it stressed also pushed
analytical attention toward the importance of broader contexts. Thus rational choice
authors (such as James Buchanan, Gordon Tullock, and Mancur Olson) introduced a range
of contextualizing concepts, such as public goods and free riders. That is, rather than
simply analyzing individual interests, such as supporting a public park, public choice
analysts stressed incorporating interactional dynamics about how decisions are made.
These new concepts led to the insight that it could be “rational” not to reveal your support
for the park, but to ride free on others with a similar interest. Examining general
“equilibria conditions” within which specific local policies (such as property taxes) are
embedded also pushed analyses in a more contextual direction. Accordingly, the nature of
rational decision making was seen to depend on the decisions of others, as developed with
baroque complexity in applying game theory to politics.
Box 6.5
That it is necessary People’s Minds should be prepared for the Reception of the best Laws.
Nothing could appear more insupportable to the Germans than the tribunal of Varus. That which Justinian
erected amongst the Lazi, to proceed against the murderers of their king, appeared to them as an affair most
horrid and barbarous.
Mithridates, haranguing against the Romans, reproached them more particularly for their law
proceedings. The Parthians could not bear with one of their kings who, having been educated at Rome,
rendered himself affable and easy of access to all. Liberty itself has appeared intolerable to those nations
who have not been accustomed to enjoy it. Thus pure air is sometimes disagreeable to such as have lived in
a fenny country.
Baibi, a Venetian, being at Pegu, was introduced to the king. When the monarch was informed that they
had no king at Venice, he burst into such a fit of laughter that he was seized with a cough, and with
difficulty could speak to his courtiers. What legislator could propose a popular government to a people like
this?
— Montesquieu, The Spirit of the Laws (1777, bk. 19, ch. 2)
Storming the bastille of elite-centric analysis. The individualistic focus of public
choice authors had another surprisingly contextualizing effect. It shifted attention from
princes, presidents, and party bosses to ordinary citizens. Democratic leaders depend on
citizen support; such leaders ignore citizen preferences at their peril and adjust their
programs to reflect those preferences. This idea was central to the writings of economistscum-political-analysts like Kenneth Arrow and Paul Samuelson. Analogously, Anthony
Downs stressed that political parties and leaders were not autonomously dominant. In a
systemic context, candidates become servants of citizens by choosing popular issues for
campaigns. Tocqueville was a further inspiration for authors (such as Robert Putnam) by
stressing how people build “social capital” (e.g., trust). Tocqueville stressed not the strong
state or the landed gentry, but small towns and their plurality of organizations, from farm
associations to churches, which articulate local political cultures.18
Think small. “Context” can be large, in the grand tradition of civilizational analysis of
Samuel Huntington, Schmuel Eisenstadt, or Francis Fukuyama, stressing massive entities
like the West or Asia, and how these civilizational “contexts” operate.
“Context” can also lead one to think small. Small units become hugely important when
we focus analytical attention on ordinary citizens and processes such as migration. As
folks move around, cities and neighborhoods acquire distinct local political histories,
cultures, and institutions, which can differ markedly from one another and from the larger
units of which they are a part. Think about San Francisco and Austin Bohemians versus
San Diego and Houston country clubs, for instance. To see these differences, we need to
consider “context” as “local context.”
Daniel Elazar is perhaps the leading recent theorist of local context. He developed his
account of American politics in some 50 books in which he elaborated a global
interpretation of local context. Elazar’s (e.g., 1975) central idea was that America’s
political subcultures trace back to the deep value commitments of the original immigrants
who settled the country. In New England, the source of these values was not geography,
but the theology of Calvin, carried from Swiss communes as well as Dutch and English
nonconformist churches. These were “covenant societies,” whose founding documents
explicitly linked the new government to God and his people. The archetype was the Ten
Commandments brought down from Sinai by Moses to guide the ancient Jews. This was
no contract between individuals; it was a God-given covenant that all must follow as a
moralistic guide in life as well as in politics.
Box 6.6
Would to God I believed more in the omnipotence of institutions! I would have more hope for our future,
because by chance we might, someday, stumble onto the precious piece of paper that would contain the
recipe for all wrongs, or on the man who knew the recipe. But, alas, there is no such thing, and I am quite
convinced that political societies are not what their laws make them, but what sentiments, beliefs, ideas,
habits of the heart, and the spirit of the men who form them, prepare them in advance to be, as well as what
nature and education have made them.
— Alexis de Tocqueville, September 17, 1853, Selected Letters on Politics and Society (1985, 294)
The New England town meeting, in requiring attendance of all adult citizens, enshrined
egalitarianism among its population. Collective action was based not on majority rule by
individuals but on consensual support among all through reasoned discussion and
compromise. Elazar contrasts this New England political culture with the cultures of the
mid-Atlantic and South. These had no covenants with God in their founding constitutions.
Mid-Atlantic settlers were more individualistic and suspicious of government intervention
into the free market. They favored majority rule by individuals, not consensus arising out
of deliberation. The South, by contrast, was more traditionalist-hierarchical. The Southern
gentleman—slave owner living in his plantation house—was the American social type
closest to the European aristocrat with his “blue blood.” Government was accordingly
seen more as a vehicle for securing hereditary privilege than for regulating the market or
reforming the world.
Over two centuries, migration and national integration via a growing federal
government and mass media have still not erased these patterns. They have been carried to
cities and neighborhoods outside their original settlements. Elazar traced these migrations
in microdetail, for instance, showing Scots-Irish moving from Appalachia into Southern
California towns like Bakersfield, bringing their “culture of honor” with them (Nisbett and
Cohen 1996). Multiple surveys and case studies still indicate such differences (e.g., Clark
2004).
Scenes and Presidential Voting Patterns
These diverse intellectual trajectories within multiple traditions of political research
converge on the simple yet important idea that national voting patterns provide a window
into the links between scenes and political ideology. Even within a single nation, there are
many and diverse local cultures, bound up with distinct political orientations and styles of
decision making. A “rational choice” differs in a traditional versus transgressive scene.19
Given its decentralized national system, moreover, such local political-cultural variation is
especially salient in the United States.
Box 6.7 Parties Transform Local Issues, but Less in the United States than
in Most Other Countries
In the United States more than other countries, the open primary elections facilitate new issues to rise from
citizens more easily and rapidly, especially at the lower levels, in mayoral or city council elections. This
local dynamic generates a highly decentralized party structure, even if the party names are identical across
US localities. The issues the major parties run on, and the policies they implement, are far more
decentralized than in the more nationally centralized administrative and party systems of most of the world.
Cities differ dramatically in local responsiveness. For instance, Clark and Hoffmann-Martinot (1998,
132 ff.) found that income and educational inequality among citizens in US cities link strongly to more
local civic activities and their mayors’ statements of policy preferences on redistribution (to favor more
spending on public health, public welfare, and public schools). By contrast in France, Germany, the United
Kingdom, Finland, Norway, Czech Republic, Slovakia, Italy, Poland, Israel, Japan, and Argentina there was
zero local political impact from local inequality. National political party positions were the main drivers of
mayors’ policy positions in these countries.
— The authors
A straightforward way to reveal the nexus of scenes and politics is to correlate them.
Figure 6.6 shows a strong overlap between county scenes and voting, highlighting voting
trends in counties with key dimensions of scenes, from the more urbane (self-expression,
transgression, rationalism) to the more communitarian (tradition, neighborliness,
formality). Most strikingly, the more urbane areas grew increasingly Democratic from
1996 to 2012. These are scenes marked by art galleries, yoga studios, coffeehouses,
environmental organizations, civic and social organizations, health food stores, travel
agencies, research and development organizations, scientific and technical consulting
firms, ethnic restaurants, and tattoo studios. By contrast, the more communitarian scenes
of tradition, neighborliness, and formality grew more Republican. These scenes are built
on fewer urbane amenities and more amenities such as churches, cemeteries, and hunting
lodges.20
Figure 6.6
This figure shows Pearson correlations between six (YP) dimensions of scenes and US presidential county voting from
1996 to 2012. County voting data come from the Atlas of U.S. Presidential Elections (http://uselectionatlas.org).
These results suggest intuitive affinities between these particular scene dimensions and
political orientations. A self-expressive scene, for instance, likely indicates a broadly
culturally liberal environment, open to mixing and pluralism, and tolerant of new and
different ideas and practices. Inglehart and Welzel (2005) argue that such self-expressive
values foster liberal ideologies at the cross-national level, and our results suggest that
similar processes occur within nations as well. Likewise, the small-town community feel
indicated by the communitarian dimensions seems strongly culturally resonant to a
conservative worldview. Simmel’s (1971) classic contrast of metropolis and village, for
instance, associated the latter with a slower pace of life, discomfort with change, and
rootedness in ways of life conserved through generations. The small town continues to
hold a significant place in the conservative imagination. For example, a 2014 Pew
Research Center survey found that 76 percent of consistent conservatives chose small
towns or rural areas as their ideal place to live, compared to just 31 percent of consistent
liberals.21 Our results are consistent with these survey results, and indicate that residents
of areas with scenes that embody the idea of local small-town community do indeed tend
to vote more Republican. Figure 6.6 also suggests that scenes and politics grew
increasingly aligned between 1996 and 2012.
Figure 6.7 throws the growing overlap between scenes and presidential voting patterns
into sharp relief. It shows the average (absolute value) correlation between the 15 scene
dimensions and Republican vote share across the five election years. The trend is
unmistakable. In the 1996 Clinton-Dole contest, the average correlation of the 15
dimensions with Republican voting was around 0.04; by the time of the Obama-McCain
and Obama-Romney races, it had grown by about a factor of three, to around 0.12. The
American political landscape increasingly corresponds to its cultural landscape.22
Figure 6.7
Figure 6.7 shows the average absolute value Pearson correlation of the 15 (YP) scene dimensions with county
Republican vote share from 1996 to 2012. County voting data come from the Atlas of U.S. Presidential Elections
(http://uselectionatlas.org).
A natural question arises when examining correlations like those in figure 6.6. Does the
overlap between scenes and national politics simply map onto and reflect ostensibly more
fundamental cleavages, such as a county’s size, affluence, or racial and religious makeup?
Evaluation of this question requires models that assess these and other politically salient
characteristics of counties. This is, to be sure, a first step. As we have stressed throughout
this book, neighborhoods within the same city can vary tremendously, and individuals
even more. A full assessment of potential scene effects on political life needs to join
scenes analysis with individual and neighborhood data, especially because the former has
been central in the bulk of current voting research. This is extremely challenging in the US
context, where the country’s vast size makes it difficult to assemble surveys of individuals
that are large enough to be meaningfully matched to local areas. However, we have been
able to analyze individuals and their surrounding scenes in Canada, with some striking
results, summarized below. Still, a first step is an important step, and the county-level US
results are highly intriguing.
Figure 6.8 illustrates the general strength of the scene-politics linkage by examining
specifically the degree to which the relationship between transgressive scenes and
Democratic voting depends on other salient county characteristics. The model includes our
main Core variables: population, rent, the nonwhite and college graduate percentage of the
population, and our cultural industry cluster variable. To these we add other possible
determinants of political differences: the 20- to 34-year-old and 60-and-over percentages
of the population, the overall religious adherence rate, the evangelical and Catholic
adherence rates,23 the number of unions per zip code,24 turnout,25 and whether the county
was in a red or blue state (defined as the states won by each party for a given election
year).
Figure 6.8
This figure shows results of multilevel regressions analyzing Republican county vote share from 1996 to 2012, where
counties are the level 1 units of analysis and states are level 2. Points correspond to fixed effect estimates, and lines show
the 95 percent confidence interval. If the line crosses 0, the variable is not statistically significant at that level.
Transgression × Rent is the multiplicative interaction term of county transgression and county median gross rent, which
is mapped in figure 6.9. N is all US counties. County voting data come from the Atlas of U.S. Presidential Elections
(http://uselectionatlas.org).
The first point to take away from figure 6.8 is that it confirms an idea we repeatedly
stress, that no single variable dominates. Many characteristics of counties relate
significantly to their partisan makeup. Republicans are often more likely than Democrats
to be in smaller, higher rent, more homogeneously white counties, with fewer younger
(20–34) and older (60+) citizens. Republican counties also tend to be home to more
religious adherents and evangelicals, but fewer labor unions; they are typically in red
rather than blue states. High turnout tends to favor Democrats. These results are consistent
with what political scientists typically find in surveys of individuals, and thus provide a
useful baseline of traditional factors against which to evaluate our scenes results.
Figure 6.8 also indicates both how durable America’s major geographic partisan
patterns are and how those patterns also show tectonic shifts. Rent, age, race, unions, and
religion are steady sources of political cleavage, and racial composition remained the
single strongest variable throughout. Yet there were some shifts over this period: for
instance, less homogeneously white areas, always more Democratic, shifted further in this
direction, especially in Obama’s elections; big cities also became less Republican.
But perhaps the most interesting shift concerns the interplay between religion and
education. Indeed, the evangelical makeup of a county changed in its political
significance, shifting steadily rightward. Catholic counties also shifted to the right over the
same period. At the same time, counties with more college graduates grew more
Democratic. In 1996, education was positively correlated with Republican voting.
However, this connection between college graduates and Republican voting progressively
shifted, until educated counties voted more Democratic in 2008 and 2012.
The shifting politics of education and religion are indeed major changes. Not only are
these changes likely bound up with the increasing alignment of scenes and voting (seen in
figures 6.6 and 6.7); they illustrate a point stressed by Robert Fogel (2000). The
politicization of American evangelicals—in one or another direction—is not constant, but
appears and recedes in waves, typically around big moral issues of the day.26 Robert
Putnam and David Campbell add specificity, showing how the recent wave of evangelical
political activism emerged in reaction to the mainstreaming of the 1960s and 1970s
counterculture, and grew out of decades of grassroots efforts, before bursting onto the
presidential scene with the election of George W. Bush in 2000. This politicization of
evangelical religion, they suggest, generated its own counterreaction, especially among
highly educated college graduates, who became both increasingly secular and politically
liberal in response. Figure 6.8 shows how deeply these shifts are reflected not only in
individual attitudes and survey responses but also in the very fabric of American partisan
geography. At the same time, as Fogel and Putnam suggest, what goes up can also come
down, and the current alignment is by no means natural or permanent.27
Against this backdrop, the results for our scenes measures in figure 6.8 take on added
salience. They show the correlation of the scene with the partisan makeup of counties,
independent of these deep and documented fissures (county size; racial, educational, and
age composition; religion; unions; and even red versus blue state location). While new to
political models, scenes, as figure 6.8 shows, are also a durable part of the American
political landscape. Indeed, in all five elections, counties with higher scores on our
transgression performance score were more Democratic and less Republican. And we
know from relations among scenes dimensions that less transgression implies more
tradition, neighborliness, and localism, which typically means more Republican votes.
Figure 6.8 suggests that the connection between liberal politics and liberal culture is not
just a by-product of more traditional political characteristics, such as education and union
concentration.
That the overlap between transgressive scenes and voting is “independent” from the
other variables in our model does not mean, however, that the scene does not interact with
these other variables. The results for “transgression × rent” in figure 6.8 indicate that they
do, in fact, interact. This variable (transgression × rent) picks out political impacts in
counties with both more transgressive scenes and higher rent. We call this pattern a
“Bobo” effect, and graph it in figure 6.9.
Figure 6.9
This figure maps the Bobo scores of all US counties. Boboness here is measured as county’s rent multiplied by its
transgression performance score. The map uses Jenks natural breaks to group counties into five bins. Positive values and
darker shades indicate counties with both above average median rents and above average transgression scores. Our
regression models include as a Bobo measure the product of the z-scores of county median gross rent and county average
transgression score. For mapping, we reversed the sign of this product term for all counties with both below average rent
and transgression. This makes the mapped value for such counties negative.
“Bobo” is short for bourgeois Bohemian, a term coined by New York Times columnist
David Brooks: the combination of Bohemian values and bourgeois budgets produces
Bobos, bourgeois Bohemians. As the children of the 1960s aged, Brooks argues, their
wallets grew but their Bohemian tastes persisted. They lived out classical themes from
nineteenth-century Romanticism, formerly limited to small circles of authors, poets, and
artists. Backpacking rather than polo; authentic peasant and ethnic food rather than
Michelin stars; drum circles, reading groups, and rock ’n’ roll rather than Bach,
Beethoven, and Brahms; Edutourism rather than cruises; and so on. Now armed with
expense accounts, these tastes could define a new lifestyle—as seen in high-end camping
and outdoor gear suppliers (like REI) in Bobo strongholds like the SF Bay Area or Seattle,
$200 ticket prices for a Rolling Stones concert, and the mixing of exoticism and
authenticity in the recipes of gourmet cooking magazines.28
For Bobos, fatter wallets thus need not imply conservative politics, but rather an
opportunity to more effectively champion the Bohemian cultural and political ideals that
had in the past been more strongly associated with marginality and poverty. Multiplying
transgression by rent is a straightforward way to discriminate high rent/high transgression
from high rent/low transgression. This “Bobo” index, rather than making Bobos a
dichotomous type, generates a continuous spectrum, so we can analyze how locations
across the country which vary in their degree of “Boboness” differ in their politics. While
other measures of Boboness are possible, this one proves surprisingly powerful and has
strong face validity, as the map in figure 6.9 shows.
Box 6.8
To calculate a person’s status, you take his net worth and multiply it by his antimaterialistic attitudes. A
zero in either column means no prestige, but high numbers in both rocket you to the top of the heap. Thus,
to be treated well in this world, not only do you have to show some income results; you have to perform a
series of feints to show how little your worldly success means to you. You always want to dress one notch
lower than those around you. You may want to wear a tattoo or drive a pickup truck or somehow perform
some other socially approved act of antistatus deviance. You will devote your conversational time to
mocking your own success in a manner that simultaneously displays your accomplishments and your ironic
distance from them. You will ceaselessly bash yuppies in order to show that you yourself have not become
one. You will talk about your nanny as if she were your close personal friend, as if it were just a weird
triviality that you happen to live in a $900,000 Santa Monica house and she takes the bus two hours each
day to the barrio.
— David Brooks, Bobos in Paradise (2000, 50)
The map shows higher Bobo scores in the San Francisco Bay Area and around Boulder,
Colorado; New York; and Washington, DC. Minneapolis, Seattle, and Portland are
relatively dark. Conversely, scores in the Midwest and South are generally low, as
expected. Bobo counties are especially concentrated in San Francisco and south of the Bay
Area into Silicon Valley. They extend north into Marin County and Sonoma County. These
areas have some of the highest housing prices in the United States and are replete with
Whole Foods stores, hiking trails, crafts fairs, and late-night drum circles on the beach.
Many Colorado counties also rank high on the Bobo scale. Pitkin County, Colorado, home
to Aspen, is in the top five nationally, and several strongly Bobo counties cluster around
Boulder. Another Bobo cluster runs along the Atlantic Seaboard and includes several
counties in the New York metropolitan area, Boston’s Suffolk County, and Fairfax and
Arlington Counties (suburbs of Washington, DC).
How closely do voting patterns line up with Bobo patterns? Republicans tend to fare
worse electorally in high rent counties with strong transgressive scenes, compared to
similar counties with weak transgressive scenes. Figure 6.10 shows this clearly. Look first
at the left side of the figure, that is, at counties with strongly untransgressive scenes. The
top dotted line stands high on the y-axis: high rent counties without transgressive scenes
had a Republican vote share well above the national average. As the dotted line moves to
the right, it descends sharply. At the far right are counties with the highest transgression
scores; here, high rent counties had Republican vote shares below the national average.29
Not all affluent counties are politically equal. High rent/high transgression counties tend to
be more Democratic; high rent/low transgression counties tend to be more Republican: a
neat illustration of how an ostensibly simple and clear basic variable for political analysis
—affluence, as indicated by high median rent—is more chameleonlike if we look closely.
Transgression is a political transformer: moving across scenes, money changes political
color from blue to red.
Figure 6.10
This figure shows how transgression and rent interact to predict lower Republican vote shares. The figure is read left to
right, where the x-axis indicates county average (YP) transgression performance scores, and the y-axis indicates the
predicted Republican vote share (in 2000). All variables have been standardized. Predicted values are based on
multilevel models with counties as the level 1 units of analysis and states as the level 2 units of analysis. Covariates
include all variables in figure 6.7. N is all US counties.
Box 6.9 Sonoma County Growers Win Emerald Cup Award
A custom cannabis strain developed in Sonoma County known as “Cherry Kola” won the Breeder’s Cup at
the 10th annual Emerald Cup cannabis competition, held for the first time ever at the Sonoma County
Fairgrounds. . . .
The proprietary strain was developed over a number of years by the Sonoma County Collective, CEO
Asa Shaeffer said. The strain also won the second place in the annual “Flower” contest, which pitted
hundreds of cannabis buds from across California in a juried competition.
“I can’t put it into words; this was an actual event where people viewed it as an honor,” Shaeffer said as
workers cleaned up from Sunday’s awards ceremony to make way for performances by classic rock bands
that included Big Brother, Canned Heat and Jefferson Starship. “Overall, we’re overjoyed.” . . .
About 4,500 vendors and conference-goers attended each day of the two-day event. . . . Conference
goers were able to browse displays with a variety of marijuana-related products, including seeds and
agricultural equipment. Those with state medical marijuana certificates were permitted to buy and smoke
marijuana as well, with no interference from patrolling Santa Rosa police officers and private security.
— Sean Scully (2013)
Context and Composition30
These results indicate the power of place in politics. Indeed, place-based ideological
differences and voting patterns are well established (Bishop 2008; Blake 1972; Gelman
2008; R. J. Johnston 1983). Yet there is little close analysis of specific social dynamics
generating these spatial patterns. Two major ways in which space matters for voting and
political ideology are through “compositional effects” and “contextual effects” (R. J.
Johnston and Pattie 1998; Cochrane and Perrella 2012; Gidengil et al. 1999), central in
recent work modeling local effects (Sampson et al. 2005; Wodtke, Harding, and Elwert
2011).
Compositional effects are driven by characteristics of individuals, commonly
demographic, which matter for a given outcome (e.g., voting). Importantly, compositional
effects trace regional political variation to the clustering of particular types of people in
particular places. They do not depend on any specific type of spatial context; regardless of
where, exactly, highly educated people cluster, the compositional effect of education will
be roughly the same. In contrast, contextual effects operate when local area characteristics
influence individuals’ behaviors, such as when demographically similar individuals who
reside in qualitatively different communities have divergent community-specific
experiences and life chances (Kirk and Papachristos 2011; Sampson 2012; Wodtke,
Harding, and Elwert 2011).
In past research on spatial differences in politics, contextual effects were often
identified simply by controlling individual-level variables. Any remaining unexplained
variation was attributed to regionalism, or the effect of place (Elkins and Simeon 1979;
R. J. Johnston and Pattie 1998). This leaves regions as empty vessels, a residual left
unaccounted for otherwise. Without some meaningful account of why living in a certain
place should inform a person’s politics, “context” resembles a placeholder waiting for an
explanation (Cutler 2007).
Scenes analysis is a way to fill up such local area vessels with substantive content and
identify mechanisms through which contextual effects operate.31 One pathway is through
shaping residential patterns and location decisions. To the extent that taste for certain
scenes is correlated with distinct political attitudes, scenes can help explain why certain
individuals cluster in one place rather than another. A second process is by defining local
norms of political sense making. Scenes can embody shared styles of attention and
judgment that influence which types of candidates and parties “feel right” to voters
(Green, Palmquist, and Schickler 2004).
This point extends into politics the Kantian insight from chapter 1: our subjective
judgments are validated when we observe others responding as we do (R. J. Johnston
1983). Such reasoning led Hannah Arendt to make the aesthetics of The Critique of
Judgment the basis of her political theory (Arendt 1992). Scenes may analogously help
individuals observe others’ subjective political judgments and have their own political
judgments validated or invalidated (Millie 2008). A neighborhood filled with art galleries,
women’s organizations, and farmers’ markets communicates and validates different
political values than a neighborhood filled with truck dealers and business associations.
The values communicated by the local scenescape set the local context, which mediates
national political events.
Aggregates and Individuals
Our US analyses already indicate strong links between scenes and politics by aggregating
votes to the county level. These county aggregate results are important in their own right,
especially for voting. We often want to know which party in an area received the most
votes, since these local aggregates determine the makeup of national legislative bodies.
Individuals come and go, yet these local aggregate patterns are often remarkably stable.
For instance, in Canada the 2001 and 2011 Liberal Party electoral vote shares correlated
0.65. In the United States, the 1996 and 2012 Republican vote shares correlated 0.72.
Yet aggregate relationships are only one type of local area process. Also crucial are
relationships between aggregate area characteristics and individual behavior.32
Unfortunately, direct tests of how local spatial context affects individuals’ politics are
difficult and rarely done because of methodological challenges. Most national surveys of
citizens are too small to permit local area analysis.33
However, we found that we could break some new ground by using an individual-level
exit poll from the 2011 Canadian federal election.34 These data are extremely valuable for
our purposes because every respondent is associated with an electoral district (ED). This
allows us to link respondents to our Canadian scenes data set and Statistics Canada
sociodemographic characteristics of each district.35
To measure individual political attitudes, we created a summary measure of the
conservatism or liberalism of each respondent’s overall political ideology. Our analysis
focuses on relating political ideology to two scenes dimensions: self-expressive legitimacy
and local authenticity. Highly “self-expressive” scenes include arts districts of large cities
(West Toronto, East Vancouver, Montreal’s Plateau Mont-Royal) while “locality” is strong
in small towns and rural areas (Saskatchewan, the Atlantic Provinces).
We evaluated the impact of the scene on individual politics against a battery of
individual- and election district–level control variables similar to those used in much past
research. Individual controls include gender, age, household income, education, visible
minority status, number of children, religiosity, political engagement on social media, and
place of residence (urban versus rural). ED-level controls are average rent, percent of the
ED population identifying as a visible minority population, percent of the ED population
with a bachelor’s degree or higher, percent of the ED population reporting no religious
affiliation, and the percent of dwellings in an ED that are rented (not owned).
Findings
A first major result is that 11 percent of the variation in individual politics is explained by
differences between election districts, and the remaining 89 percent by differences
between individual voters. Second, individual voters’ political sensibilities are associated
with the distinct scenes in which they live. Being surrounded by amenities that promote
self-expression (e.g., art galleries, live theaters, music studios) is associated with liberal
political attitudes, while amenities that emphasize locality (e.g., monuments,
campgrounds) are associated with conservative attitudes. As these effects remain
consistent when individual-level controls are added, these associations are not reducible to
individual demographic characteristics.
These findings take on further interest, since other scenes dimensions were
insignificant. Scenes of equality and the state—rooted in amenities such as immigrant
resource centers, welfare services, public hospitals, public libraries, and public schools—
show clear positive relations with Liberal voting using aggregate ED data (Silver and
Miller 2014), but were unrelated to liberal individual attitudes. This nonfinding was
surprising given that a cornerstone of modern liberal attitudes is support for government
intervention to promote social and economic equality between people and groups. Yet
these historically powerful dimensions of state and equality emerge as less politically
salient in contemporary Canada, while personal self-expression and local authenticity are
more salient. These national election results mirror our discussion of buzz, indicating how
in many locations the arts and expressive activities galvanized politics.
Contrasting contexts specifies distinct political dynamics. Traditional left-right voting
by class (stressing state and equality) often declined when new party programs like the
Third Way of New Labour and candidates like Tony Blair and Bill Clinton emerged (Clark
and Lipset 2001). Still our French scenes study of turnout in presidential elections found
that the key drivers were still mainly the traditional ones—income, occupation, and
percent immigrants. Local scenes were insignificant. By contrast, in European Union (EU)
elections, scenes measures, especially those defined by strong cultural organization
concentrations, increased turnout among the same French voters. EU elections featured
lifestyle parties and issues like the environment more prominently than French presidential
elections, and arts activity was also a more salient factor (DellaPosta et al. 2014).
Integration, Autonomy, and Polarization
How much are people swayed by scenes, politically? One common pattern emerges: moreeducated people seem less swayed by their local scenes. This holds where we could
analyze local citizen and scenes data, in Canada and Spain. We detail this for Canada.
Figure 6.11 shows how people with more education seem less responsive to their scenic
context. More education and living in a self-expressive scene both predict lower (i.e.,
more liberal) scores, and local authenticity predicts more conservative attitudes: in the left
graphic, all three lines slope down as they move to the right; in the right graphic, all three
lines slope upward; the dotted (high education) line is always lower (showing more liberal
citizen responses) than the other two lines.
Figure 6.11
This figure visualizes how the relationship between education and politics shifts across scenes in Canada. It shows how
associations between political ideology (on a left-right scale) and high (90th percentile), medium (median), and less
(10th percentile) educated individuals shift across self-expressive and localist Canadian electoral districts. The base
shows standard deviations; the vertical axis is the left-right index score. The left-right index combines five items from
the IPSOS poll, a question about what party the respondent voted for in the 2011 federal election, and four general
questions about the respondent’s political attitudes: “On most political issues, do you consider yourself to be on the
‘left,’ ‘right,’ or ‘centre’?”; “Do you favour or oppose the death penalty for people convicted of murder?”; “What is your
view on same-sex marriage?”; “Which comes closer to your view? ‘Government is doing too many things that should be
left to business.’ ‘Government should do more to solve problems.’” Cronbach’s alpha for this scale is 0.733. Analysis of
vote choice alone yields similar results to those reported in the text. See the online appendix for more details.
However, the slopes of the lines vary. Less-educated individuals show the sharpest shift
across scenes, becoming about 1.5 units less conservative between the least and most selfexpressive scenes. In the right graphic, as the environment becomes more localist (and
culturally liberal), the political views of less-educated individuals shift accordingly,
becoming nearly as liberal as the most educated. The slope for highly educated persons is
shallower, moving down about 1 unit across self-expressive scenes and barely increasing
across localist scenes. As the environment becomes more localist (and culturally
conservative), the least educated do too, but the most educated do so less—accordingly,
the political distance between the most and least educated grows. The result is that
Canada’s more self-expressive scenes are less polarized by education than its most localist
scenes—in the former the three lines draw closer together and in the latter they spread
apart. Thus the relative cultural autonomy and cosmopolitanism that education plausibly
produces may also lead, indirectly, to heightened political polarization between the most
and least educated in certain circumstances.
We report these finding to suggest that political individuation itself may be a
contextually variable dimension of social life, with potentially major consequences for
political polarization. That is, rather than presume a priori that political decisions are
autonomously individualistic or holistically collectivistic, we can analyze these two
interdependent processes and assess their relative impacts. Navarro Yáñez and RodríguezGarcía (2014) found similar scenes-individual convergence results for Spain.
Scenes and Political Contributions
Voting is a central political act in democratic societies. Yet elections are the final moment
of campaigns, and campaigns run on cash to get there. Thus, one of the most potent forms
of citizen engagement is through direct financial contributions to electoral campaigns.
With the expansion of the Internet, this form of political action has become more easily
accessible to more citizens.
Digitization has also made it easier to track where political contributions come from.
The Federal Election Commission reports information about every contribution over $200,
including the name, gender, occupation, industry, and (crucial for our purposes) zip code
for each donor. The Center for Responsive Politics has gathered all this information into
electronic files, accessible at its website, opensecrets.org. Social scientists have only just
begun to tap into it.
The analytical value of these data is potentially huge. Crucial is that they can take us
below the county to zip codes. Throughout this book, we have stressed how county
aggregates can mask neighborhood differences. Zip codes can differ markedly from their
surrounding counties politically. Fairfield, Connecticut, cast only about 43 percent of its
votes for George W. Bush in 2000. But zip code 06830 in Greenwich gave 76 percent of
the $685,000 it contributed in 2000 to Republican candidates. This was the fifth-highest
total Republican contribution from any zip code in the country, and it came from a county
where a solid majority voted for Al Gore. By contrast, Manhattan overwhelmingly voted
Democratic, but Manhattan’s 10021 gave more to Republican candidates than any other
zip code in 2000 (even if it gave slightly more to Democratic candidates). Analyzing
county voting dynamics alone ignores the political activism of fund-raising in places like
Greenwich or Manhattan.
Moreover, the dynamics of contributions may be strongly related to the local scene. It is
easier to write a check or directly deposit funds from your bank account than to change
how your neighbors vote. Lifestyle preferences encoded in scenes thus might appear in
contributions even more clearly than in voting, especially since the contributions are listed
separately according to candidates and parties, as well as political action committees, the
National Rifle Association, Greenpeace, and so on. Such value-laden contributions are
potentially rich indicators of politicized scenes, permitting us to diagnose more finely and
deeply the expressive content of local political scenes.
Combined with other scenes concepts and data, this information offers distinctly rich
ore for analytical mining that can sharpen our understanding of where and why political
contributions occur.36 Here we offer a simple illustration of the power of scenes for
understanding contribution patterns. We examine connections between “Blue Blood”
amenities (such as yacht clubs, private golf courses, and country clubs, defined more
precisely below) and the ratio of Republican to Democratic contributions in a zip code.
“Blue bloods” figure prominently in accounts of American political culture. Robert
Dahl’s classic New Haven study Who Governs? featured “social notables,” heirs of the old
“patricians” who had “founded and governed town and colony, city and state for nearly
two centuries, and who, besides, embodied the highest achievements of a Congregational
society” (1974, 17). Over time, with influxes of Catholic immigrants and the rise of “the
new men” of industrial capitalism, these patricians lost political power.
Membership in informal clubs became key markers of social standing. “One symbol—
probably the best—of membership in upper-class New Haven society today is an
invitation to the annual Assemblies held in the New Haven Law Club. . . . The Assemblies
exist to provide the attenuated version of primitive puberty rites, the social debuts of the
daughters of the elect” (Dahl 1974, 64). In the late nineteenth century, these earlier
immigrants created private schools, suburban homes, and other exclusionary institutions
like country clubs that were more blue blood than egalitarian. Paul DiMaggio (1982a,
1982b) details how the Boston “Brahmins” transformed cultural institutions like the
symphony, theater, and museum from raucous, cross-class affairs into more narrowly
genteel and elite institutions. Generally, “as new European migrants flooded into cities
like New York, Boston, and Philadelphia, as industrialization exploded and as class
tensions rose, elites began to construct institutions that could protect their families from
the threats of a modernizing nation” (Khan 2010, 6).37
Box 6.10
She: If Bush’s friends were the only ones who voted for him, we’d be much better off. Wouldn’t we? It’s
that world. It’s the same world. My father—and (she confesses) I supposed I—have the same financial
interests as Bush and his father. But they’re not friends—I wouldn’t say that.
He: They don’t socialize?
She: There are parties both go to.
He: The country club?
She: Yeah. The Houston Country Club.
He: Is that the club for the bluebloods?
She: Yes. For the nineteenth-century bluebloods. The older Houstonians. A lot of debutante balls take
place there. They’re put on parade. There’s a swirl of white.
— Phillip Roth, Exit Ghost (2007, 207)
The political meaning of “blue-bloodedness,” however, is complex. Harvard—a historic
Brahmin bastion—already in the late nineteenth century expanded admissions beyond
New England elites.38 In the early twentieth century, creation of the house system
explicitly mixed rich and poor. Harvard thus outpaced other Ivy League institutions in
reducing WASP exclusivity. At the same time, some leading Cambridge lights brought
new cultural themes into play. For instance, William James hosted séances and lectured on
self-transformation and self-expression—ideas that fueled the “consciousness raising” of
the 1960s New Age movements. Irish Catholic John F. Kennedy mixed with blue bloods
and married former “debutante of the year” Jacqueline Lee Bouvier in Newport, Rhode
Island, home to many New England patricians. Yet Kennedy was an iconic liberal
Democratic president. The Bobo pattern emerged from roots like these, to spread across
the United States and other parts of the world.
Newport by 2000 combined Blue Blood amenities and weak electoral support for
George W. Bush. Our analysis (not shown) of links between Blue Blood amenities and
county voting patterns reveals such Blue Blood political complexity. Counties with
numerous Blue Blood amenities generally vote Republican. Yet when Blue Blood
amenities combine with strong self-expression and local authenticity, the Blue Blood–
Republican connection is reduced to the point that Blue-Bloodedness does not predict
voting in any meaningful way. Like the Bobo analyses, this illustrates the contingency of
the seemingly foundational variable, income, when one or two scenes indicators are added
to standard voting models.39
Methodologically, the Blue Blood index illustrates another way (beyond the
performance scores and interactions discussed above) we can use amenities to measure
important sociopolitical concepts. We can go back to our basic amenities for more
conceptually pure components than the more general scenes dimensions like glamour, and
construct new measures that join with powerful models used by many others. Our Blue
Blood index illustrates one way to do this. It is a simple sum of the number of skiing
facilities, boat and yacht clubs, cigar shops, Episcopal churches, equestrian clubs, golf
courses, private golf clubs, Presbyterian churches, private tennis clubs, private clubs, and
ballroom and social dance instruction services. Table 6.4 shows the 25 US zip codes with
the most Blue Blood amenities, their total contributions to each major party, and the 2000
Republican vote share for their surrounding counties.
Table 6.4. Top 25 Blue Blood zip codes
Presidential campaign
contributions ($)
Zip Placecode name
Blue Blood
amenities
Democratic
candidates
Republican
candidates
Republican vote
share (%)
33040
Key West, FL
140
17,325
14,900
49
32541
Destin, FL
102
3,000
28,860
75
34102
Naples, FL
96
7,300
111,375
67
40383
Versailles, KY
94
2,000
11,150
60
40511
Lexington, KY 82
1,000
15,000
54
10001
New York, NY 69
18,300
10,750
15
96761
Lahaina, HI
65
2,000
2,300
33
34231
Sarasota, FL
60
2,750
8,200
53
19102
Philadelphia,
PA
59
19,000
26,500
18
30303
Atlanta, GA
57
10,000
26,900
41
34482
Ocala, FL
54
0
2,350
55
29926
Hilton Head
Island, SC
50
4,200
25,900
59
92663
Newport
Beach, CA
50
10,500
68,526
58
33125
Miami, FL
49
0
2,250
46
34134
Bonita
Springs, FL
49
3,950
40,000
59
89101
Las Vegas, NV 48
9,200
8,500
47
02840
Newport, RI
47
6,500
6,050
41
33301
Fort
Lauderdale,
FL
46
21,700
72,225
31
96753
Kihei, HI
45
702
5,050
33
33602
Tampa, FL
45
16,000
29,350
52
40507
Lexington, KY 45
1,500
12,400
54
33401
West Palm
13,400
34,925
36
45
Beach, FL
36561
Orange Beach, 44
AL
250
2,750
74
96740
Kailua Kona,
HI
43
0
3,950
34
34145
Goodland, FL
42
1,000
16,350
67
92660
Newport
Beach, CA
42
2,1950
252,844
58
Note: This table shows the US zip codes with the most Blue Blood amenities, together with the zip code’s total
contributions to Republican and Democratic presidential candidates in 2000 and their surrounding county’s Republican
vote share in the 2000 presidential election. The Blue Blood amenities index sums: skiing facilities, boat and yacht
clubs, cigar shops, Episcopal churches, equestrian clubs, golf courses, private golf clubs, Presbyterian churches, private
tennis clubs, private clubs, and ballroom and social dance instruction services. Contributions data come from the Center
for Responsive Politics (opensecrets.org).
Many top Blue Blood zip codes are in the South, especially Florida but also Hilton
Head, South Carolina; Lexington, Kentucky; Orange Beach, Alabama; and Atlanta,
Georgia. These zip codes are joined by some big-city downtown areas (in Philadelphia and
New York) and Hawaii vacation spots. These top Blue Blood zip codes provided far more
financial support to Republicans, about 77 percent, although Republicans won only 49
percent of the votes in these counties. Golf mecca Pebble Beach, California, is a good
example: only 37 percent of its county (Monterey, home to ex-hippies, farmers,
dot.commies, and more) voted for Bush, yet Pebble Beach gave 91 percent of its $63,600
in presidential contributions in 2000 to Republicans. Newport, Rhode Island, again stands
out among the top Blue Blood zip codes in contributing more to Democrats than
Republicans, along with Key West, Florida, Manhattan’s 10001, and zip codes in Las
Vegas, Los Angeles, Washington, DC, Chicago, and San Francisco.
Box 6.11
Pebble Beach, California, is home to Cypress Point golf club, the second-ranked course in the world,
according to Golf Magazine. Bob Hope (a longtime member) once joked: “One year they had a big
membership drive at Cypress. They drove out 40 members” (Golf.com 2015).
— The authors
To control for multiple causes of political contributions, we used our Core zip code
model in figure 6.12. To this we added the Blue Blood index at three levels: the zip code
total number of Blue Blood amenities, the average number per zip code in the county, and
the average number per state. We then used a three-level multilevel model, which registers
how zip codes and partisan contributions may cluster by counties and states.
Figure 6.12
In this figure, the line represents results from a single multilevel model where variables measuring the presence of Blue
Blood amenities have been constructed based on different areal units. The model utilizes the Core, using census 2000
variables where possible, and includes Republican vote share in 2000. To compare results, all variables (including
outcomes) have been standardized. The y-axis shows regression coefficients indicating the association between Blue
Blood amenities and partisan presidential contributions at the zip code, county, and state levels. Partisan contributions
are measured as the ratio of Republican to Democratic contributions during the 2000 election cycle. Presidential
contributions data come from the Center for Responsive Politics (opensecrets.org).
Figure 6.12 focuses on the ratio between Blue Blood amenities and partisan
contributions at the zip code, county, and state levels while controlling for the other
variables in the model. The pattern is clear: the line starts high on the left, but then
declines as it moves to the right. County Blue Blood amenities provide less information
about zip code presidential contributions, and states provide nearly none.40 Clearly,
analyzing counties and states leaves out important zip code attributes that cut across both
levels and are often quite strong—a nice illustration of the potential of adding small localarea data for scenes and amenities to clarify cultural sources of political activism. We are
accordingly exploring political contributions to PACs, such as the National Rifle
Association, human rights groups, environmental groups, and more, to better understand
how they join in the political dynamics of scenes.
Conclusion
This chapter shows clear connections between the cultural and political character of
places, and that the strength of these relationships tripled for presidential elections from
1996 to 2012 (cf. figure 6.7). For politicians and political activists, these results document
the importance of targeting messages to more than red and blue states or rich and poor
voters. Political messages may be interpreted quite differently in counties with different
scenes, even when counties are similar in wealth and many other standard political
correlates.
For political analysts, these results suggest the need to elaborate political cultural
specifics below regional and state levels to include county and zip code variations. They
also show the value of employing a wider set of cultural indicators, beyond church
attendance or single amenities such as Starbucks and Walmart. Including hundreds of
amenities permits us to measure subtle but important cultural differences and to gauge
their political impacts with a precision and sensitivity surpassing much past work on
political culture.
Many familiar ways of discerning political tendencies retain their importance in our
results. Republicans do well among the affluent; Democrats, in ethnically diverse big
cities. Evangelicals have mobilized politically in recent decades, with important but
complex impacts, while college graduate concentrations increasingly have aligned with
Democratic voting.
Yet there is more to the American political landscape than these classic variables.
Republicans do well where the scene is less transgressive and more traditional, local, and
neighborly, regardless of the local population, rent, racial and religious makeup, and the
other standard political variables in our models. New social movements emerged in the
1970s, and their bases of support remain distinctively narrow, even four decades later.
They are concentrated in areas with dense, urbane, educated, artistic, diverse, selfexpressive, walkable scenes—and even more so when walkability and self-expression
coexist. Yet some NSM values have spread more broadly. We capture them with scenes
measures like our Bobo index of rent × transgression. Counties that are more Bobo are
less likely to vote Republican than are other affluent counties—bourgeois budgets are
shifted by Bohemian sensibilities. Counties where Blue Blood amenities are plentiful tend
to vote Republican, but the Republican–Blue Blood connection weakens in more selfexpressive scenes. Our analysis of impacts on political contributions by Blue Bloods,
measured at state, county, and zip code levels, documents that zip code impacts surpass
impacts of the same Blue Blood items measured using state and county averages. Smaller
is often bigger, for political analysis.
Finally, our analysis of the interplay between individuals and their environments in
Canada is one of the only direct empirical tests of the qualitative dimensions of local
cultural context on individual political attitudes of which we are aware. Our findings are
therefore important, even though the effect of cultural context is small relative to the effect
of individual characteristics. A corollary for contextual analysts (like geographers) using
primarily place-based data follows: include data about individual characteristics as well as
context; conceptualize and analyze autonomy and integration, holism and individualism,
as interdependent processes.
7
Making a Scene
How to Integrate the Scenescape into Public Policy Thinking
The primary concerns of this book have been descriptive and analytical: What are scenes,
how can we measure them, where are different types of scenes, and what are their
consequences? Policy implications have emerged here and there, but people whose
primary interest is in public policy will likely want to know more: What can I do with
these ideas for my community? This chapter offers some general advice for integrating
ideas about the scenescape into public policy thinking.
These policy issues are not idle questions for us. We have actively participated in the
policy process, in particular in Chicago and Toronto. These experiences inform much of
the discussion throughout this chapter.
The focus of the chapter, however, is less on specific policy suggestions and more on
outlining how to use scenes ideas, concepts, and data in policy making in ways that others
can adapt to their own circumstances. That scenes are generally important for urban policy
is not news to most policy makers—far from it. In fact, many mayors and city officials
have been decades ahead of academics in recognizing how significant scenes, or more
broadly the character and feel of their cities and neighborhoods, can be for the fortunes of
their communities. And they know how important policy decisions, about zoning or
housing or business licensing or noise or grants, can be for preserving, enhancing, or
changing that character.
The approach developed in this book helps further advance understanding of the policy
implications of scenes in two ways: first, to articulate a way to think about the general
importance of scenes, in the context of some of the major challenges policy makers face
today, as one key issue area among others; second, to show how local “character” can be
measured, quantified, and eventually translated into specific policy goals. The scenescape
thereby moves out of the realm of ineffable “quality of life” and stands alongside the
major concerns that have long dominated policy discussions, like education, income,
density, and population changes.
This is a novel and useful contribution to urban policy. Planning departments and policy
consultants, if they so choose, can incorporate scenes measures into their cost-benefit or
other analyses along with jobs and income. Ask for these if you are making policy. Most
of our data are available down to the zip code level and are publically available to
download if others wish to use them, even if tapping other sources may be useful as well.
We begin by detailing critical changes in the past few decades that have shifted the
foundations of urban policy, giving cultural issues in general and scenes in particular
heightened policy salience. Some discussion draws on earlier chapters, but here we stress
relevance for policy makers. Crucial is the idea that even if different cities and
communities operate in a similar general context, they must make decisions based on their
own specific histories and needs. There is no one right answer, and what works in San
Francisco might not work in Indianapolis. It is thus crucial for any city or community to
compare itself to others (or subsets of others) along many dimensions and to evaluate the
implications of adopting one course of action over another, while at the same time
undertaking more focused study of one’s own locality.
Based on these general ideas, some practical advice follows about how to include
scenes-style thinking in formulating urban policy, both nationally and locally. Next come
some examples of results that can follow from different policies, highlighting the
connections between self-expressive scenes, density, and college graduates. The chapter
concludes with lessons from Toronto, where certain scene-related concepts have been
integrated into official cultural, economic development, and land-use policy making.
New Challenges for Urban Policy
Many basic challenges of urban policy have critically shifted in the past three to four
decades. Globalization, individualization, gentrification, postindustrialization—under one
label or another, these processes are staples of many general accounts of urban
development. What is new here is explicitly joining them and drawing out their
implications for policy makers. The most general result of these changes from our point of
view is that urban policy cannot avoid serious consideration of scenes—how to identify,
expand, diversify, focus, and protect them so as to energize civic identity; grow, retain,
and attract talent; draw visitors; and build strong neighborhoods. A few words follow on
each change process and how it links to scenes analysis.
Globalization. While analyses of globalization often focus on its economic dimensions,
like outsourcing, finance, or free trade, just as important are its cultural and political
consequences. Policy decisions proceed less in isolation and more in constant comparison
to what people around the world are doing.
Chicago provides a telling example of this social-psychological effect of globalization.
The traditional Chicago political machine operated through an army of precinct captains,
taking marching orders from their particular bosses, all the way up to the Boss Himself,
Da Mayor. Television coverage in the 1980s, however, intruded into the inner sanctum of
Chicago city hall and the council chambers. Visitors to Chicago would comment, for
instance, that they knew all about that night when Mayor Washington’s successor was
chosen, since they had seen it on TV in Norway!
This global audience in turn increased the mayor’s and council’s consciousness of their
worldwide images, as non-Chicagoans became part of what sociologists call a “reference
group” that now extended the world over. That is, leaders would not just ask, “What do
Chicagoans think of this vote and of me?” but also “What do others outside Chicago
think?” The public images of the city and its leaders, broadcast worldwide, became a
direct concern for the mayor and citizens. Media advertising, publically available
accounting standards, and efficient service delivery (rather than payoffs) increasingly
drove Chicago politics, and thus policy, in the 1990s. The sister city program was
expanded. Maggie Daley, wife of the Mayor Daley II, would bring home ideas about
urban design from Paris (like wrought iron signs at subway stops and flower gardens on
major boulevards), and the mayor would ask his staff to think about how Chicago might
incorporate them. That is, what happened and what people thought in Paris, New York,
London, and Tokyo mattered in Daley Plaza, in ways they had not before.
Chicago is of course not alone in this regard. Many policy makers are now highly
sensitive to the ways in which their communities relate to the wider world. Such
comparative thinking can sometimes provoke efforts to catch up with perceived global
standards by building amenities that “any competitive” city “has” to have: a natural
history museum, a contemporary art museum (preferably designed by a renowned
architect), an aquarium, a new symphony hall, and the like. Others add (or sometimes
pursue instead) their distinct local specialties to contrast themselves with the rest. Flint,
Michigan, won a prize for a walking tour which even local residents said taught them
much about their hometown. Mayor Daley II declared that the banks of the Chicago River
should become more cultured than those of the Seine; and he hired Chinese speakers to
teach Mandarin in Chicago Public Schools. Indianapolis built cultural corridors linking
historic neighborhoods while it made its downtown a center for motor sports tourism and
conventions. New York City made Times Square a pedestrian zone.
Other examples are in boxes. The general point is that globalization faces policy makers
with a set of questions about civic identity. Who are we, what image of ourselves do we
want to project to the world, and what audiences are drawn to that image? What do we
have here that is similar to and different from elsewhere, and how can citizens, potential
new residents and businesses, and possible visitors find out about that? There are no easy
answers to these questions, but they are on the table now in a way that is hard to avoid.
The tools in this book provide powerful ways to consider them more deeply and precisely.
Mayors or planners can assess and measure how their city or neighborhood differs from or
is like others within and across contexts, and decide based on that information what
amenities and scenes to focus on.
Increasing options. More people’s lives proceed with a strong sense of what we called
in chapter 1 “contingency.” This is another way of saying that the path one takes is not
given in advance but is experienced as variable and open. Yes, we are all born into a given
nation, town, extended family, religion, and from parents with specific occupations and
educations. But the question more and more is, where to go from here? To stay or go is
being asked by citizens in ways that policy makers have to address daily.
Many cities have focused directly on the group where this sense of contingency seems
most visible: the young and talented recent college graduates, the centerpieces of “the
creative class.” They change jobs frequently and are more footloose and fancy-free than
most. But still, they change cities less often than they change jobs. Thus a critical decision
after college or graduate school is where to locate. Policy can reach out to them as citizens
and residents who might prefer to change jobs locally rather than moving elsewhere or use
help in launching new small firms.
On the other side of the equation, following a major drop in the birth rate after the baby
boom of the 1950s, cities and firms are now in serious competition for talent (domestic
and foreign) to replace retiring baby boomers. To keep the talent they have, and to bring
more from elsewhere, they have to make a case that it is worth moving here and staying,
that there is something that makes life here more enjoyable, fulfilling, animated. Hence
the international spread of policies designed to build and promote amenities and scenes
that might be attractive to the younger and single members of the creative class, who are
often thought to be both the most innovative and the most likely to make amenities a
centerpiece of their location decisions. But the young and talented are not the only
residents, and elected officials who respond too visibly to any one group can alienate
constituents who feel left out.
Box 7.1 Making a Local Scene in Louisville
On the local food scene:
It’s been an interesting way to see how the rural parts of the state and the metropolitan areas really
appreciate the partnership that we have with our local food movement. Like many places around the
country but particularly here, when you go into restaurants, you’ll see the origin of the food in terms of the
farmers that they came from. We were the first city in the world that we know of to do a demand analysis
for local food, how much local food do people want to consume here. We did that deliberately to help our
partners in the rural areas of the state, the farmers, so that they can understand that they’ve got a big,
growing market in the biggest city in Kentucky.
When we did this survey, no matter what somebody’s socio-economic background was, everybody
supported local food. They said, a), it’s healthier and b), we want to help local businesses. So, it kind of
busted this myth that local food, farmers markets, all this was just a yuppie kind of thing. Everybody
appreciates good local food.
On why a 2014 college grad would choose Louisville over other cities such as Cincinnati or Nashville:
One, you want to take a look at the culture of the city. Are you going to be able to fit in? Are you going to
be able to make a difference? You know, not every city is perfect for every student. So, is there a
connection? Do you like our art scene? Do you like our local food scene here? What about the innovation
we’re doing with the makerspace, for instance? Because I think we’re among the best in the country in that
regard.
Take a look at the economic development clusters that are important to a city. In our case, are you into
lifelong wellness and aging care, or food and beverage, or logistics and e-commerce, or business services,
advanced manufacturing? Where is that fit for you? I can guarantee if you’re going to live here, you’re
going to have a good quality of life and enjoy yourself, but are you going to be able to be employed in a
meaningful way?
Any city that says they’re everything for everybody is being disingenuous. It’s just like a company.
When you look at the city, find a place whose values mirror yours and whose opportunities mirror your
interests at the same time. Make sure it’s got a beautiful, natural environment like we have here that’s full
of nice people, and then you’ll have a good place to live—and it would be nice if it was Louisville.
— Interview with Greg Fischer, mayor of Louisville (2014)
A city’s scenes—overall and within certain neighborhoods, and jointly with job
opportunities nearby—are crucial factors in this competition for young talent, as chapter 5
demonstrated in considerable detail. From a policy perspective, if “getting a good job” is
the goal, the neighborhood scene is a critical context for defining what counts as a “good
job.” A job in or near a vital, engaging scene is often a “better job” than the “same” job
elsewhere.
The general point is that as options and comparative shopping for locations increase, the
direct market value of scenes becomes more pronounced. It would be a mistake, however,
to conclude that this point holds only for the young, affluent, and college graduate
members of the “creative class.” Retirees, as we showed in chapter 5, are locating in
places with better access to natural amenities and the arts. And baby boomers show some
of the strongest sensitivity to scenes; their numbers have risen in places that emphasize
personal self-expression and local authenticity, like Sonoma, California, or Asheville,
North Carolina. Retirees and boomers bring disposable income, neighborhood stability,
and high levels of civic activism and volunteerism. And given their size, in numbers and
aggregate purchasing power, policy makers ignore the movements of the nonyoung at
their peril.
Similarly, as chapter 5 showed, the African American population is increasing in
neighborhoods with a range of nightlife and entertainment options and many smaller
churches, both more traditional Baptist and newer denominations. These scenes speak to
deep and powerful biblical themes, like egalitarianism and charisma, but also to the
excitements of seeing and being seen. Bronzeville, Chicago, exemplifies this pattern, but
neighborhoods in Atlanta and Memphis, and also elsewhere, are leaders as well.
Neighborhood groups, like Revival: Bronzeville, have sought to enliven the local scene
with arts, culture, and sport, not only to bring new residents and give them reasons to stay,
but also to build a sense of community engagement and neighborhood pride among those
who are already there—to become a place to be, not only to be from. Artist Theaster Gates
has developed new ways to cultivate neighborhoods’ scenic potentials through innovative
interventions into urban space.
Box 7.2 Town Sees Fame in the Gold of Daffodils
Lindenhurst may have finally struck gold in its struggle to find an identity apart from its proximity to
Gurnee Mills and Great America. In anticipation of the village’s 50th anniversary of incorporation next
year, local leaders designated the golden daffodil as Lindenhurst’s official flower and recently distributed
50,000 bulbs to create a blanket of yellow across the north suburban town in springtime.
“The idea is when spring comes, they all come alive and the town will go golden,” said Mayor Jim
Betustak. “We’re hoping to take it statewide, and maybe we can become the daffodil capital of Illinois.” If
nothing else, planting the flowers may finally put Lindenhurst on the map and bring recognition to the
bedroom community of about 14,000 residents that is named for its many linden trees.
A relatively young town compared with others in Lake County that are more than 100 years old,
Lindenhurst does not have a historic district or a town square, and leaders have struggled to make it a
destination for area residents.
“When you have a newer community, you have to create an image,” Betustak said. “Now people may
say, ‘Let’s go out to Lindenhurst in the spring because of the daffodils.’” . . .
Volunteers for the village distributed five bulbs to each of Lindenhurst’s roughly 4,000 households. . . .
The remaining 30,000 bulbs were given to the Park and Fire Districts, schools and other public entities,
officials said. “We want them all to be part of this community project,” Betustak said. “Everyone can
participate.” . . .
Down the street, Di-Ve Garcia said she was surprised by the plan. When children recently piled out of a
mini-van to deliver her bulbs, she assumed they were selling cookies.
“I thought, oh, how odd,” said Garcia, 37. “But it will be neat to see all of the houses with yellow
daffodils—that will be something.”
Other residents said they believe the flowers will create more than just a beautiful sight. They also will
unify the community and put Lindenhurst on the map in a positive light.
“Everybody has festivals, and they put up clock towers and stuff,” said John Miller, who has owned
Linden Barber Shop on Grand Avenue for more than 30 years. “A clock tower is nice, don’t get me wrong,
but it’s in one place. The daffodils will be everywhere. And after a while, people forget about the clock
tower, but they’ll see the daffodils all over every spring.”
— Courtney Flynn (2005)
Lindenhurst’s daffodils project won an award from Urban Innovation in Illinois (UII), formed by Terry
Clark with civic and professional groups to feature local innovations via local press coverage, presentations
by the key innovators to their professional colleagues in the region at the conferral of the award, listing on
websites, and so forth. UII is a local branch of Fiscal Austerity and Urban Innovation, which helps with
similar efforts in 35 countries (www.faui.org). Several points in this chapter come from examples
elaborated by local participants.
— The authors
At the same time, not only global cities, like New York or London, competing for
investment bankers and star musicians, but also smaller towns, looking to draw and retain
residents, are increasingly active in thinking about how to create compelling scenes that
differentiate them from others. Promoting community gardens, inviting artists to display
their work and perform in public buildings like libraries and city hall, facilitating
neighborhood walks or bike rides—these are relatively inexpensive ways to build civic
pride and increase citizen engagement; scenes like these give reasons for choosing this
place over others.
Chapter 4 showed that within specific contexts local authenticity is linked with urban
development. To repeat the comment by Mayor Brainard of Carmel, Indiana: “We don’t
have the Pacific Ocean, we don’t have the Rocky Mountains. So we have to work harder
on our cultural amenities and in our built environment to make it beautiful—and to make
it a place where people want to choose to spend their lives, raise their families, and retire”
(Brainard 2009). Size and natural endowments are not destiny; as chapter 4 showed,
Mayor Brainard was not alone: locally authentic scenes in locations with moderate to low
access to natural amenities are nationally significant in key development outcomes like
increases in postgraduate shares of the population. Similarly, local authenticity is linked to
growth if people walk more. Policy can make a difference: communities without
mountains can work to present what makes them locally distinctive. Pedestrian-friendly
streets encourage more people to stop and enjoy the local fare.
Box 7.3 How an Artist Creates a Scene
Gates was trained as a potter, but his artistic practice includes, among many things, sculpture, musical
performance, installation and something that has been called large-scale urban intervention. Around the
corner from the bank, on the 6900 block of South Dorchester Avenue, he bought and restored a half-dozen
other vacant properties as part of what has become his Dorchester Projects. He filled one building with
14,000 volumes of art and architecture books from a closed city bookstore and 60,000 19th- and early-20thcentury glass lantern slides that the University of Chicago no longer wanted. He refitted the building with
wood from a former North Side bowling alley, the varying grains and textures of the exterior boards
composing a dramatic tapestry. Inside the house next door, he put all the vinyl LPs from Dr. Wax, a South
Side record store that went out of business. Another property became home to the Black Cinema House, a
venue Gates dreamed up for movie screenings, discussions and neighborhood film classes. Young, creative
people and longtime inhabitants of the area live in other Dorchester Projects housing; Gates lives on the
block as well. . . .
Gates sometimes describes his work as reimagining the possibilities of “black space.” Could a block of
decaying two-flats well beyond the city’s cultural and economic hubs be converted to form a new creative
cottage industry? Could artistic types be drawn there and made to think of themselves not as gentrifiers but
as entrepreneurs with a stake in the African-American community? When Mayor Emanuel spoke to me
about Gates, he called him a civic treasure on par with Chicago’s skyline and downtown museums.
“Theaster is creating a culture zone, a cultural central point on the South Side,” Emanuel said.
— Austen, “Chicago’s Opportunity Artist” (2013)
When we discovered the overlaps between Gates’s holistic style of work and our scenes perspective, we
started consulting with him to help generalize his message to other locations. Several YouTube videos
illustrate his ironic combinations of multiple themes, through sculpture, song, and lecture. His work is
inspiring artists and urban planners alike.
— The authors
The general point here is not to hold to one specific policy but to adapt policies by
keeping in mind multiple types of groups and individuals who make decisions about
where to live with local amenities in mind, including families (not only singles) and the
less hip postgraduates (not only young college grads): not only schools, parks, and
churches, but also day care, farmers’ markets, karate clubs, skate parks, and more. Some
specific examples of small- or midsize-city initiatives are in boxes; these speak against the
widespread idea that rising mobility and contingency are disasters for all except superstar
global cities like London or New York.
The rise of culture. Robert Putnam’s Bowling Alone became a best seller with the
argument that participation in voluntary organizations like Kiwanis or the Boy Scouts has
steeply declined since the 1950s. It warned of dire social consequences on the way. More
people would live as isolates rather than as active members of their communities.
However, even if some organizations have lost members, others have gained. We found
a marked increase in the number of people who are members of arts and culture groups.1
Young and low-income persons have increased their arts participation the most. The
pattern varies internationally, with the United States, Holland, Canada, and Sweden
showing the steepest increases. And it varies across and within cities and metro areas, as
we have documented throughout this book. Still, the rise is quite far-reaching. And the
level and increase of arts participation and engagement are probably much larger than
most official data suggest, due to undercounting of very small arts groups and omitting
many popular art forms and new forms of engagement, such as through digital media.2
This rising interest in arts and culture has major policy consequences. More cities are
developing official cultural policies and undertaking cultural planning exercises.
Municipal cultural affairs departments are growing, in size and confidence, sometimes
building bridges with economic development and planning departments.
The shift is most striking in cities with a stronger Protestant history, in which “serious”
issues like work, school, and church, and “bourgeois” virtues like thrift and delayed
gratification have historically been more central to political culture. Boston is one of the
most dramatic cases in point, as are other cities like Minneapolis, Seattle, and Portland.
Instead of circumscribing the arts behind high or countercultural walls, they now are more
likely to encourage the arts. Further, the arts are increasingly recognized as a potentially
key element of urban development, attracting tourism, investment, and new firms and
residents.
As more leaders and citizens acquire a more open attitude about the arts, a whole range
of cultural policy concerns gains new salience. Arts grants are still central. But so are
broader policies directed toward the vitality of the local scene: cleaning up dirty
waterfronts, planting flowers, painting murals, holding festivals, slowing traffic,
encouraging walking, promoting performances and exhibitions in public spaces, and
loosening up or at least streamlining permitting processes for these and similar activities
(like mobile food trucks that serve interesting cuisine)—these are some of the policies that
many places have pursued to help make neighborhoods into attractive and engaging
scenes, which residents and many visitors can enjoy.
At the same time, as more political leaders and officials become more aesthetically open
and sensitive, grassroots and minority arts and cultural groups can become less
marginalized and oppositional, since they can offer distinctive cultural contributions. Such
groups can have a major seat at the table in policy discussions. If they can organize
themselves and develop a coherent voice, they are more likely to find political leaders
ready to listen.
The bottom line is that precisely how and in what direction to galvanize and connect a
city’s cultural resources is an open question—but whether a city should do so is far less
controversial than a decade or two back. Mayors and cities are building on arts and culture
faster and sooner than most social scientists and journalists report. These are new and
dramatic changes for most everyone in North America, albeit less so internationally.3
Diversifying patterns of urban growth. From the 1950s through the 1970s, many big
US cities experienced “white flight”: higher-income people of European ancestry would
leave mixed-income, mixed-race inner-city neighborhoods for homogeneous suburbs and
exurbs. The big city became a symbol of neglect, blight, and danger; the suburb, of
wholesomeness and family. These images have been the subject of intense cultural
scrutiny in film, novels, and television shows. Migration patterns have also changed. More
young, affluent, educated, white persons are moving to central cities. It would go too far to
call this shift a reversal of suburbanization or a general victory of urbanism over
suburbanism: sprawling Sunbelt cities like Phoenix, Atlanta, and Houston are still among
the national leaders in total population growth; suburbs, and Patio Men, as David Brooks
called them, are alive and well. But the “back to the city” movement is a dramatic change
nonetheless, as many inner-city neighborhoods that were “off limits” to many have seen
increasing demand, new development, new amenities, rising rents, and greater racial,
educational, age, and occupational diversity.
“Gentrification” is the label often used to describe these changes in migration patterns.
It is a helpful term, as far as it goes. It indeed focuses policy attention on influxes of
demographic groups who for decades had avoided city living. And it helps to raise the
question about what the best response to the changing character of many neighborhoods
should be.
At the same time, “gentrification” as an analytical term has its limits, as we discussed in
chapter 5. The main problem is that the term presents what is a complex, multidimensional
phenomenon as a narrow economic process, where the (active) rich look for cheap rents
and drive out the (passive) poor. No doubt this happens, but much else is also at play.
“Gentrifiers,” for instance, are not always white—Chicago, Atlanta, and Washington, DC,
among other places, have had notable cases of “black gentrification,” which changes the
dynamic between “newcomers” and “old-timers” in ways that go beyond rich versus poor.
Nor are “gentrifiers” always affluent; many are recent college graduates without steady
jobs or children; many come from middle-class families, but others do not, as in the
example of “blue-collar Bobos” in Bridgeport, Chicago (see chapter 5), or Asian
immigrants in Flushing, New York.4
Moreover, the choice about where to live includes far more than rent, as chapter 5
showed. Proximity to various scenes, to downtown, neighborhood amenities, public
transportation, and much, much more are in play. Cheap rent plays a relatively small role
per se in this equation—the decision is as much cultural as economic. And while many
children of the suburbs are moving to cities, many suburbs are taking on a more distinct
urban cast, with denser and more-walkable districts, and “big city” cultural amenities of
their own, like performance halls and museums. Suburbs moreover are now the
destination of the majority of immigrants to the United States, and increasing numbers of
African, Hispanic, and Asian Americans live in suburbs (cf. Lloyd 2012). Broad social
and cultural changes are afoot, which go beyond one well-defined and well-bounded
group displacing another.
Just as important is the fact that current residents and those labeled gentrifiers
themselves are not passive victims of an inexorable process. There are many ways to
actively intervene; the story is not written in stone. We reviewed several in chapter 5, but
the point bears repeating here. Strong neighborhood associations can work to keep
newcomers out, just as they can work with them to integrate new and old; and many of the
children of the “old” are themselves part of “the new.” Arts groups can (and have) lobbied
city hall to enact policies designed to preserve artist live-work spaces as new, nonartist
residents arrive. Newcomers themselves can value the historical character of the
neighborhood into which they are moving, including its distinct human ecology, and
organize “social preservation” efforts. There are religious dimensions as well, as in the
case of Atlanta’s Robert Lupton, a Presbyterian minister whose urban ministry collective
seeks “gentrification with justice” (Hankins and Walter 2012). There is no one-track
model, but many, many possibilities, none of which are foreordained, and all of which are
results of action or inaction.5
The implication again is that responding to diverse patterns of neighborhood change is a
widespread policy challenge with no single answer. But it is a challenge that must be met
somehow. That is, if many smaller towns face the challenge of how to build scenes that
attract new and retain current residents, many big-city neighborhoods have a different
“problem”: they have some of the world’s most dynamic scenes, people are flocking to
them, and they need to figure out what to do about this dramatic increase in demand. It is
an open question whether this means loosening or tightening development restrictions,
subsidizing affordable units and artist live-work spaces, building more parking spaces or
pedestrian zones and public transportation, high-rises or mid-rises, or some or all of the
above, or something else entirely. Different solutions may work better in different places.
But some decision has to be taken. And whatever it is will have big consequences for the
direction in which a city or neighborhood unfolds, and for the types of scenes it has to
offer going forward.
In general, then, the actors and concerns described in many past policy discussions (like
gentrification or suburbanization) omit or downplay many new factors and processes
featured in this volume. It is thus crucial to pay more attention to these new processes and
concerns, which affect increasing numbers of citizens: festivals, flowers, walking, biking,
public art, and the like. These policies can build and transform scenes, shifting the
dynamics of gentrification and suburbanization, one neighborhood at a time. To capture
these multiple dynamics means focusing on more than narrowly economic incentives like
tax write-downs. To be sure, business leaders themselves often care a lot about tax
incentives. But their employees—and they themselves as residents—are likely to be
animated by other, more wide-ranging concerns for amenities and scenes. Businessoriented magazines like Fortune or the Economist now routinely include some measure of
culture and “liveability” in their various city rankings, for instance.6 How, then, to
specifically develop policies that acknowledges these shifts?
New Directions in Urban Policy
Policy now proceeds in a transformed landscape—global, comparative, culturally infused,
with growth centers and fallows in and out of inner-city neighborhoods. Actively
including serious thought about the character of a city’s or neighborhood’s scenes is
clearly a part of this new terrain. We do not propose any specific policy as better or worse
—this is part of the relativist perspective encouraged by sensitivity to multiple scenes and
their distinctiveness. Instead we offer some advice about how policy makers can make
their own informed decisions about what is best for them, first at national or state levels,
and second at local levels.
Two general principles guide these recommendations, both of which flow from the
general orientation of this book: contextualize and cultivate. Rather than adopting any
purported one-size-fits-all solution, whether a corporate headquarters, new museum, or the
like, think of urban policy as a process of cultivating the latent potential of a city or
community, somewhat on the model of a gardener. Look around and see what types of
scenes are already present, what activities are already animating your streets and strips,
and think about what it would take to grow and strengthen these. There are almost always
many seeds already present—in the form of active and interested citizens, businesses,
resident groups, and so on—whose energy only needs to be channeled in civic directions.
In many cases building up your strengths on the ground may involve adopting some
best practices from elsewhere. But “adopting a best practice” from a scenes perspective
means thinking about how that practice may fit together with and mutually benefit what is
already there, much like a painter must decide whether adopting a new technique or
adding a new figure will harmonize with the other elements of the scene. Here is where
the second principle fits in: pay attention to context. No city, no neighborhood is an island;
each has its own unique identity that comes into sharper view in comparison to others.
This is why we often compare the scene in every US zip code to others or subgroups of
others, not only in terms of amenities, but a whole host of variables relevant to policy,
from population to density to education and beyond. From a policy perspective, this
approach permits local officials to in effect travel around the whole country without
leaving home, learn how their cities, their neighborhoods differ from and are similar to
others, and evaluate the development consequences.
Higher-Level Policy
At higher levels of government, achieving most local policy goals, at least in fiscal terms,
implies transferring funds to local governments. Local governments are closer to social
problems and citizen concerns. Higher-level governments have better access to funds, yet
many are hesitant to transfer these resources to local governments without strings attached
in order to account for and evaluate the effectiveness of local spending. And sometimes
national, state, and provincial officials feel they should reset local priorities.
The challenge, then, is to give local governments room to respond to the local problems
and concerns to which they are most sensitive while maintaining more general
accountability norms so as to assess whether funds are being spent wisely. One common
solution is for experts, who survey a large number of cases, to identify “best practices”
that others might adopt, like testing public school students. Yet best practices often fail to
transfer from successful locations. Why? The context or assumptions for the best practices
are often weak or absent. This implies that policy makers must be highly attentive to how
their situation is similar to or different from those in which other policies have been
developed, and think about how to adapt accordingly. How to do so?
Build on successful scenes and integrate them into existing programs. There are lots
of small examples that work. Look for specific types of institutions and program areas that
have grown and are successful, especially new areas like arts and culture but also sports
and park programs from basketball to dance to pottery. In Chicago, for instance, many
such programs were joined with the public schools in a seamless afternoon program that
continued with the Park District after school for a few hours each day. Toronto city
officials work with community partners to incorporate unique cultural spaces into social
housing, such as recording studios, music practice rooms, and performance spaces. While
funding cuts are often challenging, in many cases they have spurred parents and neighbors
to spend their own money. The number of day care programs the world over has been
increasing, and much of their “agenda” is arts and culture for the young, complementing
the “hard work” of the schools.
There is a common theme to many of these organizations: namely, citizen
empowerment. These organizations seek to engage people with activities they already
enjoy and to channel that energy into work, school, and community, as well as personal
growth. Recognizing the social value in such groups means explicitly acknowledging that
education has to be more than memorizing the three Rs. The arts, for instance, are a
quintessential arena for teaching innovation and collaboration as growing out of “play,”
and beginning to link it to advanced creativity and cooperation in every field. Joseph Yi
(2009), in God and Karate on the South Side, shows that for many youth, black, white,
and Hispanic, karate clubs impart an engaged, participatory ethos, demanding that their
members perform and achieve at ever-higher levels, building tight, cross-racial, crossclass personal friendships that cement participants together and forestall deviance.
Learning how to support scenes replete with these self-empowering organizations is
central for developing the sort of wide-ranging education policies that can help young
people do well in a world in which creativity and personal expression are key to success.
An example of national policy moving in this direction is the “creative placemaking”
initiative of the National Endowment for the Arts initiated by NEA chairman Rocco
Landesman and elaborated in a white paper by Ann Markusen and Anne Gadwa
Nicodemus. This initiative is intriguing for a number of reasons.7 It led to ArtPlace
America, which created partnerships between the NEA and nonfederal organizations such
as the US Conference of Mayors and the American Architectural Foundation while at the
same time building links with other federal agencies (eight in all) such as the Departments
of Housing and Urban Development, Transportation, and Health and Human Services.
And it attracted significant funding from nongovernmental sources. Grants were redirected
toward arts initiatives designed to support distinct places. In subsequent rounds grants
went to proposals with nonarts partners, like botanical gardens, religious and scientific
organizations, farms, educational institutions, and even the US Army. At the same time,
other nonarts agencies started to include the arts among their priorities, with, for instance,
the Department of Education including arts language in its Promise Neighborhoods
application guidelines.
Other jurisdictions have experimented in similar ways. The State of Michigan
sponsored a Cool Cities annual conference and offered prizes for specific local programs.
The City of Chicago required that every city department incorporate some type of arts
activity into its regular programs. This even led some (historically aloof) police officers to
perform in improv theater alongside neighborhood youths; laughing at the awkward cops
reportedly built neighborhood solidarity. Boulder, Colorado, prohibited many national
franchises like “big box” retail stores deliberately to counter “Hollywoodization” and to
encourage local artists, architects, and entrepreneurs. Not all are resounding successes, but
that is the nature of experimentation. The key is to learn and adapt.
Be open to intermediaries. This is how many “new” programs have originated—with
good ideas from below. But it would be a mistake to pick one single, consistent policy or
program to apply equally to all places. One size fits all is preordained to failure (e.g., a
federally mandated karate club on every street corner). Uniformity is what gave past
national government programs their worst reputations. Such uniformity led many
countries to transfer much of their welfare state activities to lower-level governments,
even if the tax power of the national government leads in funding.
Box 7.4 For Healthy Aging, a Late Act in the Footlights
What kind of old age will you have?
Many of us look forward to spending retirement expanding our world—traveling, trying what we never
had time to do, taking classes that give us new knowledge and skills. These activities are not only desirable
in themselves, they help us to live longer and healthier lives.
But they are not within everyone’s reach. Absent money and a sense of possibilities, retirement can
become more time to fill with television. “We see people without money, who had very hard lives, who are
not aware of their own potential,” said Maureen Kellen-Taylor, the chief operating officer of EngAGE, a
program in the Los Angeles area that provides arts and other classes for some 5,000 people—the vast
majority of them low-income—living in senior apartment communities. “They just had to get through life,
taking care of things, and the idea of following a dream was not on their radar screens.”
That’s why the Burbank Senior Artists Colony is remarkable. Opened in 2005, it is a mix of market-rate
and low-income apartments. The building looks like an upscale hotel but is built for the arts, with studios, a
video editing room, a theater and classrooms.
Residents may arrive with no previous artistic experience or skill as an artist—but artists they become.
The theater group that Sally Connors participates in is working with a troupe in London, via Skype, to write
and perform a soap opera. . . . Residents work with students from a nearby alternative high school to do
improv theater, make claymation films and art from recycled items. . . .
A study done at the University of Southern California found that more respondents in EngAGE programs
reported that their health had improved in the past year, while in a control group, more people reported that
their health had worsened. A study carried out by Century Housing, one of the top lenders to EngAGE’s
communities, put a dollar figure on the gains. In the program, it found, 25 percent fewer people than in
comparable groups needed expensive interventions such as nursing care. The savings came to about $9,000
per year per resident.
EngAGE gets its money in part through fund-raising, but two-thirds of its income comes as payments
from the senior complexes where it works. These buildings, in turn, stay afloat mainly through federal tax
credits for low-income housing, said Huskey. The program is highly competitive, and projects are more
likely to win tax credits if they have a local financial contribution—for example, from the Los Angeles
Community Redevelopment Agency, or from banks, which by law must invest in their communities,
including in low-income areas.
— Tina Rosenberg (2012)
The most respected programs by local governments were those with the fewest strings
attached, with general revenue sharing and some broader categorical grants in the lead.
But there must be some strings, and the difficulty in conforming to them can make life
challenging for the huge numbers of very active small and fragile organizations that are
transforming and animating cities and neighborhoods. Especially in low-income areas,
these small organizations, often held together by a few committed members, can play a
major role in making scenes with big social payoffs: activating community pride and
imparting transferable skills like self-discipline, focus, creativity, teamwork, and selfexpression.
Such groups are often woefully underfunded. Part of the underfunding flows from a
concern by governments and foundations that the small organizations (some are too small
even to become official nonprofits) are not able to “manage” or “account” for grants
properly, exposing the grantors to potential scandal or investigation. There are enough
difficult past cases to lead many potential grantors to stay with safer, larger grantees.
One potential solution is to develop or expand existing efforts by intermediary
organizations. Good examples are the South Shore Bank and Chicago Community Trust,
and similar small local foundations, which obtained funds from individuals and
foundations and channeled them to small outfits. ArtPlace America is a national example.
Making awards to intermediate-level organizations like these and creating others such as a
neighborhood arts coordinator are potential options. Such intermediate organizations could
write checks to smaller groups under their umbrellas and serve as buffers between the
demanding national accounting standards and the flexibility of individual organizations
that cannot afford accountants and lawyers to do everything necessary to keep procedures
legally correct.
Box 7.5 Public Art in Detroit Builds Safer, Stronger Neighborhoods
Asked to conjure up an image of “outdoor art,” most people will picture an oversize abstract sculpture
sitting on the lawn of an institutional building. But in Detroit, art that is integrated with the city’s buildings,
lots, alleys, homes, and streetscapes is an integral part of the community—a vigorous, and even essential,
part of daily life.
Art that merges with the landscape brings human presence, safety, and physical activity into the city’s
spaces. This kind of art triggers more than one sense: it is something you move in, touch, and, in some
cases, even eat.
In Detroit, a spread-out city of single-family homes that is difficult to traverse and pockmarked by
vacancy, these artistic interventions are an uncommonly powerful nexus of community life. They create
welcoming traffic, as well as opportunities for neighbors to interact and work together. And rather than
being a temporary show, in the style of a traveling exhibition or ephemeral installation, this is art for the
long-term. It is for a city with a future.
This is unfolding in a residential neighborhood north of Hamtramck, sometimes called Banglatown for
its large Bangladeshi population. Here, the Power House Productions community is nesting.
Gina Reichert and Mitch Cope are Detroit artists who bought a home here in 2002 in what was once a
corner store. Over the ensuing years, the foreclosure crisis hit hard and put the community in a precarious
spot. “The neighborhood could go either way,” Reichert said.
The couple began to purchase vacant homes in the area at auction, and they have since built them into a
multi-faceted artistic community.
The one dubbed the “Play House” has become a community performing arts center. The “Sound House”
began as a recording project and continues as a public recording studio. The “Squash House” is being
converted into a venue for play and gardening, with a venue designed specifically for squash, racquetball,
and other games. The “Skate House” will merge with the Ride It Skate Park to create an indoor/outdoor
skating facility. The original “Power House” produces its own electricity from solar and wind power, while
modeling the broader power of self-reliance and problem solving. And the “Yellow House” is where
visiting artists and residents can stay and work. Reichert and Cope still live in the same home, now with
their young daughter.
Artists buying houses for creative ends is not a new story, and Detroit in particular has a long legacy of
public and place-based based art: nothing bothers Reichert more than erasing what’s come before. But
Power House does have a unique texture to it. Unlike The Heidelberg Project, the famed found-art
installation on a residential street that began in 1986, Power House is not about creating spectacle. Instead,
Reichert said, “It is about integrating in the cultural fabric of the neighborhood here.” . . .
There is something inherently democratic about this sort of art. “We want to show what arts and culture
can do,” Reichert said. . . . Part of what it can do is make the community safer. “All our properties were
vacant, bottom-of-the-barrel pieces of real estate that nobody wanted,” she said. By changing the physical
spaces—painting the building, cutting the grass—residents “can see something other than that there, and
that someone’s paying attention.” Those physical spaces also create a stimulus for talking to neighbors, and
spaces for neighbors to talk with one another.
“What art can do is start conversations,” Reichert said.
— Anna Clark (2014)
Participate in regional planning. Many local policies do not get implemented even if
strongly desired. Certain types of investments or programs demand too much money or
too long a time perspective to justify to taxpayers. Others affect and might benefit an
entire region, but for this very reason are not enacted locally because each city is worried
about the others free riding on its efforts.
Regional transportation is a classic instance. Each locality in a bigger region is likely to
benefit from a coherent public transportation policy, but none has a direct interest or
ability to make it happen. Regional tourism policies are similar, as individual cities within
regions have much to gain by developing suites of amenities that complement rather than
compete with one another and by disseminating a common message to potential visitors
about what the region has to offer. Federal and state governments can be key mediators in
these areas.
Major development initiatives are similar. They can sometimes take decades, passing
through successive local political regimes, none of which can lay claim to “delivering the
goods.” For this reason, Toronto’s massive, 30-year waterfront redevelopment project is
being overseen by a special agency, Waterfront Toronto, which was created and funded
jointly by the city, province, and federal governments, and acts with relative autonomy.
This is one example of the sort of higher-level intervention that can be crucial in
supporting scenes that affect entire regions. Of course, regional planning bodies are no
panaceas—they open up their own challenges, as new policy players can create new
vested interests and new conflicts.
Be an information hub. Federal and state governments can help spread information
about locations and their scenes to enhance the quality of choices by individuals and firms.
The US Census Bureau and other agencies do this presently, but they could do more to
provide information about available amenities and consumption opportunities across US
cities and neighborhoods, together with information about environmental quality, access to
nature, and the like. Such information is absent or not readily available in the census. But
it can be crucial for many families and businesses in determining where to locate and for
local officials in assessing their own locality’s offerings relative to others. Federal
agencies could play a more active role in encouraging tourism, providing more
information to potential visitors, as well as new residents, from inside and outside the
United States. Other countries, especially in Europe, have more active cultural
observatories and collect more data on tourism. Yet in the United States, for example,
there is virtually no data on local tourism reported systematically by the federal
government. This book illustrates the types of data and analyses that could be expanded
and refined.
Local-Level Policy
National, state, and regional policies typically operate at a level that is too general to make
direct decisions about what specific types of scenes, amenities, and organizations to
promote and protect. At these higher levels, funding, tax exemptions, vision statements,
and the like are the main policy tools. Local policy makers, however, make many
decisions that directly affect their scenes—about zoning, land use, cultural district
designation, parks, parking, pedestrian zones, and public transportation, as well as liquor,
patio, noise, or street performance permits. And there are also the specific tools of urban
cultural policy, such as arts grants, festivals, or artist housing, which directly affect local
scenes as well.
Still, many policy-making decisions even among local officials are macro and top
down. They often aim at a general policy for all, like a new convention center to spur
economic growth. Yet most local areas contain considerable internal diversity. No doubt
some areas have homogeneous policy preferences, but most do not. It is therefore crucial
to consider policies that can respond to diverse, neighborhood, scene-specific concerns. A
policy that is highly effective in a self-expressive scene, like building a tech cluster, may
not work very well in a traditional or neighborly scene, which may benefit more from
different amenities, like karate clubs or skate parks or community arts centers. This
internal diversity makes it especially important to formulate policy while considering
views from below, from average citizens. How to do so?
Look more specifically for examples of all 15 dimensions of scenes in your locality.
If some seem largely absent, ask if you want to add them, or decide which to pursue.
Smaller areas especially should be modest and focus carefully. Be prepared to build on
strength, and highlight those salient to local participants. But look a bit, and maybe ask
around, before deciding that there are no citizens who want X, especially if this implies
policies that you may not be pursuing. Any policy under consideration can be assessed in
its impact along the 15 dimensions described in chapter 2; they offer a broader framework
than most current cost-benefit analyses. They add consumption to production criteria. That
is, they encourage thinking not only about who wants to work here but also why they
would enjoy living here.
Conduct an inventory of your local amenities and how they compare to other
locations. Even if you know every church and restaurant and park in town, almost no one
knows how the numbers and types compare to other locations across the region. Our main
data are publically available and can be accessed by request. Specific groups provide
details in their areas, like restaurant associations or sports leagues. Ask related questions:
Where do citizens go for Saturday night or the weekend? How many leave town? What
attracts them elsewhere that might be added locally?
Build on distinctiveness and strong local resources. Examples include a church,
talented League of Women Voters, and great high school football team. Consult with
participants/experts about how their activities might be used better and possibly
generalized to other neighborhoods. Assemble ad hoc teams to review a range of policies
and report back (e.g., on how to rebuild on a vacant land site). In choosing team members,
consider including participants representing many if not all 15 dimensions. That is, if you
are building a skate park, bring parents and skaters and graffiti artists and nearby residents
to the table. Encourage incorporating multiple scenes perspectives if not in one project,
then across several projects.
Drive slowly, or better, walk or bike around your whole local area, stopping to talk
to neighborhood residents. Look for scenes that engage or enrage different sets of
citizens. Ask them what scenes they cherish or abhor, and how to improve. Moreover, ask
not just about a restaurant, but what else nearby makes it a destination—parking,
shopping, the people, the view, pollution, crime, music, street cafes, and so forth. These
are the components that build a holistic scene. Ask your staff or colleagues and friends if
they could do the same, say, for one week, then meet and confer. Many mayors do this
regularly, taking notes on what to change. Professionals can be engaged to do surveys in
depth, but assess the terrain yourself first and listen to local folks with experience. Ask
about what failed in the last decade, and why, as well as about new successes nearby.
Consult the Internet for new ideas that might work locally; look for examples of
activities/amenities for all our 15 scenes dimensions that might fit locally, and assess if or
how they could be supported in your area.
“Talk to people” may not seem like a very radical cultural policy suggestion; but it
contrasts rather dramatically to other approaches, which often begin from the top. Since
the scenes approach begins instead from on-the-ground activities, it encourages policy that
begins there as well. Start, that is, with what residents and visitors already enjoy and are
energized by, and think about how to grow from there. Think like a movie director, not
like a military general.
Know the local rules of the game. Some US cities are closer to the historic European
capitals of culture, like Paris, Berlin, or Vienna—deeply engaged with the arts and scenes
ideas, looking for details and specifics. Others need to be convinced of basics: the value of
amenities and scenes at all. Be aware of where each of your communities stands, and
calibrate your policy proposals accordingly. Where basics are at issue, specificity can
distract from the big picture; where specifics are needed, grand visions can be vacuous.
Attend as well to the dynamics of local political culture. As we showed in chapter 6,
new social movement (NSM) organizations (e.g., for environmental and human rights)
thrive in specific local contexts: urbane, walkable, self-expressive, artistic, dense. Outside
such urbanist settings, NSMs are rare, and their associated agendas may be met with
bewilderment, indifference, or resistance. Policy pushing for avant-garde arts, glamorous
scenes, and entertainment districts may seem alien and dangerous. Instead themes of
neighborhood and community may be more effective, such as neighborhood festivals,
walks, and gardening. The support of community leaders like school principals and local
business owners may be key. Likewise, where local politicians, rather than activist
organizations, tend to initiate policy from the top, linking the public benefits of scenes to
their personal reputations and electoral success can be important. Know the context, and
think about how to frame scene ideas to maximal effect.
What Impacts Can You Expect from Building Your City’s Scenes?
None of these remarks are meant to be too surprising; they only codify for exploring in
your area what many mayors and officials have already been doing for some time.
However, this policy case for scenes and amenities often confronts the assertion that they
are too soft or intangible for bureaucratic planning frameworks. The scenes methods and
data in this book provide an opportunity for culture and amenities to join the traditional
“harder” variables of urban and community policy, like budgets, density, population, or
crime. And, as this book has shown, the consequences of scenes for the fortunes and fates
of localities can be major. Showing this with numbers can be a crucial policy lever.
Consultants often assess potential policy impacts by showing “multiplier effects” that
come from adding a new museum or sports stadium. These predictions are typically highly
unreliable when based on one single organization like a stadium and often without an
adequate comparative basis. One major advantage of our approach is that it combines
hundreds of indicators to provide a read of the overall scene. We stress not just
considering, say, a convention center but heightening or changing the overall feel of a
neighborhood or city and assessing impacts against every other neighborhood in the
country.
This approach implies considering projections based on scenes data using economic
cost-benefit types of tools. For instance, we find that in general a 10 percent increase in
the degree to which a neighborhood’s scene promotes personal self-expression is
associated with nearly a full percentage point increase in the share of the population with a
college degree (e.g., from 5 to 6 percent)—even accounting for other variables in our Core
models, population, rent, education, race, and more. While a one-point increase may seem
small, a host of research shows that this sort of difference is major compared to most other
policies.
Of course, this is ceteris paribus—all else equal—and all else is rarely equal. For
instance, given that self-expression is typically (but not always) negatively correlated with
tradition, boosting self-expression may create conflict. In these places, one might generate
more support by linking the scene more closely to local authenticity, which is often
positively correlated with both self-expression and tradition—small galleries, local poetry
readings, nature walks, heritage, church painting groups.
For places that already have strong self-expressive scenes, it may make more sense to
focus on increasing access to these scenes and connecting them to related media, culture,
and technology businesses. Some potential options are public transportation, more
intensive residential and employment development, reserving below-market rentals for
artists and the needy, and innovation hubs that put arts groups, tech firms, design firms,
social advocacy groups, and the like in the same building. In such policies it is crucial to
be sensitive to how new development might alter the character of the scene and to listen to
its spokespeople. If no one is vocal, go out and find them.
Figure 7.1 shows the potential this sort of approach holds. In zip codes with relatively
low concentrations of self-expressive amenities, density does not bring increase in the
college graduate share of the population. But high density and high self-expression
combine to draw college graduates. Figure 7.1 graphically illustrates how this relationship
between population density and changes in the college graduate share of the population
shifts across self-expressive scenes. Start on the left, showing zip codes with low selfexpression scores. The dotted line indicates that high population density has an impact of
0—density does not increase college graduates. Now look at the far right, at zip codes
with highly self-expressive scenes. Here density is strongly connected to college graduate
gains—dense zip codes in self-expressive scenes saw an average increase of around 2.5
percentage points in their college graduate share of the population, whereas college grads
in less dense, self-expressive zip codes increased by under 1.5 percent. In other words, for
places with scenes that are already highly self-expressive, increasing density may be an
effective strategy to enhance the power of the scene.
Figure 7.1
This figure shows how the impact of population density on change in the college graduate share of the population shifts
across self-expressive scenes. The figure is read left to right, where the y-axis indicates the predicted change in college
graduate share of a zip code’s population from 1990 to 2000 (accounting for our Core variables), and the x-axis indicates
the degree to which a zip code’s (BIZZIP) self-expression performance score is above or below the national mean.
This is a simple example to help assess impacts of just density and one dimension of
scenes, self-expression. Look through other chapters for examples with other dimensions.
There is of course no substitute for judgment, and judgment is always situation specific.
But you can make informed judgments by comparing your city or community to others
and thinking about how your scenes are similar and different. Yet no matter where you are,
the character and direction of your city’s scenes can help inform policy discussion—not
just as a narrow “arts” question but instead as linked with the overall economic, social,
and cultural development of your community.
A Toronto Example of How to Integrate Scenes into the Policy Tool Kit
It is one thing to think about scenes and local policy. It is another to integrate such
thinking into a city’s formal policy-making processes. Here the hard slog of bureaucratic
reports and policy meetings, as well as political savvy, networking, and public relations,
are indispensable and unavoidable. We report here on lessons learned in helping integrate
aspects of scene concepts into Toronto’s official development policies.
Historical Background, or How Toronto Embraced Expressive Culture
First, some quick background shows how much Toronto has changed economically,
politically, socially, and culturally. These changes mirror many discussed above, but in a
specific local context.
Economically, especially since the early 1990s, manufacturing jobs have declined,
service and finance occupations have grown, and the postindustrial “creative occupations”
from fine arts to graphic design to technology and R&D have rapidly grown. Socially,
waves of immigrants have settled in Toronto, bringing with them new cultural traditions.
Starting in the mid-1950s and 1960s, a first wave was from Southern and Eastern Europe.
They were followed by countercultural Americans, escaping the Vietnam draft. Others
have come from Asia, Africa, and the Caribbean in steeply rising proportions and absolute
numbers through the 1980s and 2000s. At the same time, the city’s average household size
was declining, especially in the central city. Politically, in the late 1990s, the City of
Toronto was amalgamated with five of its suburbs. Previously connected in an awkward
two-tier metro-city arrangement, the new “megacity” instantly became the fifth largest in
North America.
Box 7.6 Pavement to Parks
San Francisco’s “Pavement to Parks” program creates spaces for people by reclaiming excess roadway,
through the use of simple and low-cost design interventions. What’s innovative about these parks isn’t so
much the design as the implementation. As Andres Power, urban designer at the San Francisco Planning
Department explains, because there is no structure in place to do something like this “it fundamentally
changes the old impasse of years of planning and just lets the space evolve over time.”
Pavement to Parks was given particular impetus by the success of similar projects in New York City,
especially the recent transformation of Broadway from 47th to 42nd Streets, and 35th to 33rd Streets,
where plazas and seating areas have been created in excess roadway simply by painting or treating the
asphalt, placing protective barriers along the periphery and installing movable tables and chairs.
Similarly, PTP begins with the goal of “transforming a sea of asphalt,” says Power. A pro bono designer
(one hopes a budget will emerge to pay designers for their efforts) works on each park (there are 12
scheduled to be finished through 2010; three have just been completed) with the mandate of using materials
the city already has to maximize greenery and, says Power, “transform a sea of asphalt.”
This approach diverts resources that would have gone to landfill and keeps the budget of these
interventions low. Composted soil comes from city landscaping and plants are either donated or purchased
at cost. Volunteers, typically community residents, are mobilized to plant, motivated by the desire to
beautify their streetscape and meet their neighbors. And as part of Mayor Gavin Newsom’s initiative to
provide edible landscapes throughout the city, fruit trees will be planted at each location. The plantings also
add storm water management capacity to streets. . . .
. . . The first of the three projects involved the least intervention: Public Architecture at 17th and Castro
transformed an unsafe and confusing intersection into a sidewalk café by simply blocking the area off with
planters.
Though two pedestrian islands were depaved for the Castro project, the Pavement to Parks model is
designed to be reversible, and pavement is typically undisturbed. The effort reflects a “renewed interest in
what our streets might look like,” says Power, as well as “a pent-up desire to create public space.”
These plantings and plaza aren’t just about aesthetics: the expanding array of planting projects along
with other traffic calming measures, dedicated pedestrian enforcement stings and new traffic signals, the
collision rate for the 11 blocks on Guerrero between Cesar Chavez and Randall Street, where the San Jose /
Guerrero park is located, has been reduced by 53 percent since 2004.
— Allison Arieff (2009)
These economic, social, and political changes have a cultural component.
Postindustrialization means more people working in and around the arts; international
competition for skilled workers has led civic and political leaders to promote the arts and
culture as a carrot for attracting globe-trotting young and dynamic creative workers. New
immigrants have introduced diverse culinary and cultural traditions, from cappuccino to
roti. Shrinking household size has increased demand for public spaces of sociability and
enjoyment outside home and family, like restaurants, plazas, cafes, and music venues. The
birth of the megacity spurred initiatives to make Toronto a “world-class” city, with its
cultural offerings centrally featured.
The most visible consequence has become known as the “Cultural Renaissance.” Most
notably, star architects Daniel Liebeskind and Frank Gehry produced strikingly
controversial designs for two of Toronto’s most traditional cultural institutions, the Royal
Ontario Museum and the Art Gallery of Ontario. But the “rise of culture” is broader and
more deeply integrated into Torontonians’ daily experience than a few redesigned
buildings.
Since 2001, Toronto has seen dramatic increases in a host of cultural and expressive
organizations and amenities. Nearly all are growing at rates faster than total businesses.
Some much faster: for instance, interior designers and dance companies more than
doubled between 2001 and 2009.
Ernest Hemingway wrote a column for the Toronto Star in the 1920s and regularly went
back and forth between Paris and Toronto. He once complained, “How I hate to leave
Paris for Toronto, city of churches.” There are now in Toronto more holistic health
centers, acupuncturists, yoga studios, and martial arts schools per postal code than there
are churches and religious organizations.8 Daily life, that is, takes place increasingly
outside of the traditional venues of the bourgeois, Victorian culture that historically
defined Toronto, which was termed in the past Hogtown for its industrialism and Toronto
the Good for its Victorian moralism.
Local arts activism rose in the early twenty-first century, with an increasingly active
cultural affairs agency, enhanced by a merger with the city’s Economic Development
Division. Civil society activists are vocal. BeautifulCity.ca organized lobbying efforts to
impose taxes on billboards, with revenue earmarked for the arts. The ArtsVote movement,
which proclaims, “I am an artist and I vote,” holds mayoral debates and issues report cards
about how arts friendly candidates for city council are. They exercise classic pressure
group tactics, targeting key districts where bloc voting by the rising number of people
working in (or married to those who work in) the arts can make the difference in lowturnout elections.
Lessons of From the Ground Up
With more residents, businesses, politicians, and civil society groups active in the cultural
field, the role of the arts in the city’s economy and residential communities became hotly
debated. Silver’s (2012) “Local Politics in the Creative City: The Case of Toronto”
explores two cases. One, discussed in chapter 6 of this book, centered on a residential
neighborhood with abandoned streetcar repair barns: Should it be torn down to make room
for a traditional grass-and-trees-and-playground park, or turned into artist housing,
exhibition and performance space, a farmers’ market, community food bank,
environmental education center, and more? The other case highlights a grassroots and
independent artist community, where many young artists had for a decade occupied former
industrial spaces and warehouses. Rents were rising, condos were coming in, and the arts
groups and supportive businesses organized in the name of “good planning” that would
preserve a foothold for creative and cultural work in the neighborhood as more and more
people arrived.
Figure 7.2
Source: From the Ground Up: Growing Toronto’s Cultural Sector (Silver 2011b). Courtesy of the City of Toronto and
Tara Vinodrai.
Both cases show on-the-ground political disputes that energize policy questions with
passion, making the character of the local scene into a matter of controversy and dispute.
While these disputes ended in ad hoc settlements with little direct official policy influence,
they pressured city officials to more tightly link cultural policy with land-use planning. In
other words, they started public discussion and conscious consideration of what makes
places distinctively engaging and attractive—they sparked explicit policy discussion of
scenes.
The question was thus raised in city hall of how to build a policy infrastructure that
would make protecting and expanding the city’s scenes a general concern across the city’s
neighborhoods, together with classic issues like height, zoning, and density. This focus on
place was not entirely new. Cultural Services in the last decade had grown increasingly
involved in planning issues, hiring for the first time a former planner, who then
collaborated with local architects, in ways that dovetail with the scenes approach, to map
all of the city’s cultural facilities and categorize them by uses, such as showcase or
heritage or incubation. But these connections between culture and planning gained extra
urgency as they took center stage on the local political scene.
A working group had been meeting, of which Silver was a part, called Placing
Creativity. At the initiative of the Economic Development and Culture Division, some
participants in this group produced a report, From the Ground Up: Growing Toronto’s
Cultural Sector (Stolarick et al. 2011; Silver served as editor and coauthor). One of its
major goals was to generate new tools based on hard data that would pass muster with
Ontario planning regulators while also building a platform for integrating cultural issues
into the municipal planning process. It also had to convince potentially skeptical city
councilors and citizens.
The report has three main chapters: (1) “Economic Analyses of Toronto’s Cultural
Sector,” which charts trends in cultural sector jobs relative to other sectors; (2) “Cultural
Location Index,” which maps where Toronto’s cultural workers live and work, as well as
where cultural facilities are; and (3) “The Economic Importance of Cultural Scenes,”
which explains how concentrations of cultural activity create added economic value while
illustrating these processes via case studies of particular people and places, highlighting
how creative people help make vibrant scenes and vibrant scenes help creative people to
do their work better.
Rather than summarize the report, which can be downloaded, consider some general
lessons that come from the process of producing it.
Bring together people with multiple types of expertise. Collaborators included
geographers, architects, cultural planners, sociologists, graphic designers, and urban
designers, as well as key figures in the local music and more broadly independent art
scene. This improved the overall quality of the work while generating credibility—
professional, academic, cultural—from multiple sources. It is an example of bringing
some of the many scene dimensions together. The report moreover was initiated and
coordinated by the economic development side of Economic Development and Culture,
not the culture side. This gave it additional credibility as speaking to “hard” rather than
“soft” issues and opened doors that might otherwise have remained closed.
The fact that meetings were held at the Martin Prosperity Institute (MPI), an
independent academic think tank, was key in this regard. It provided a neutral space
comfortable for all participants. The MPI is Richard Florida’s main research center, and
the opportunity to interact with him and his associates was likely attractive to many
participants. City and provincial officials from different departments who rarely interact
could meet outside of city hall and engage in freewheeling discussions. While not every
city has a Richard Florida, most cities are near a university, where academics can mingle
with policy makers and other cultural policy stakeholders at coffee klatches and the like,
which can blossom into more serious collaboration. Museums or art centers are other good
venues.
Providing the opportunity for cutting-edge work is also important. For the academics,
these meetings were an opportunity to work with data in ways that are new, even relative
to specialist journals. For instance, we analyzed separately both where arts and cultural
workers live and work, which is relatively uncharted territory from a research perspective.
Designers got to experiment with new types of maps and data-presentation techniques.
Planners felt they were pushing their discipline’s boundaries. Artists got to discuss
theories with intellectuals and articulate their role in the community. This interaction
creates more excitement among participants, since it engages their professional creativity
and imaginations in addition to their civic activism.
Make it pretty. A team from the Ontario College of Arts and Design University
(OCAD) made glossy foldout maps as well as a limited number of poster-size maps.
Aesthetics matter. Many folks are drawn into the ideas because they are drawn into the
beauty of the presentation. Posters can be distributed to city councilors or others to
display. This gets people used to talking about the importance of culture in the city and
gets them to think about why it differs across locations. A simple idea that could work in
many contexts.
Work is changing, not only declining. Many politicians see empty factories and
warehouses and conclude that jobs and industry are leaving the city. They infer that
residential and retail development is the only way to reanimate the inner city. While these
matter, the report demonstrates that in Toronto, though large-scale cultural goods
manufacturing (like printing or record production) is declining, the cultural sector in
general and especially its creative core is rapidly growing, more so than other key growth
areas like finance and biotech.
Much of the city is reindustrializing rather than postindustrializing, in other words.
Acknowledging this difference changes our view of the possible: an empty warehouse or
big-box store, for instance, transforms from a blight to an opportunity for experimenting
with new ways of linking work, residence, and play. Zoning the warehouse out of
existence forestalls this creativity. The general, transferrable point is that what might be
bad news from one perspective can be good news from another. Be open to many
perspectives.
Cultural clusters are often under the radar. It is easy to find a finance district: just
look for the corporate logos. Tech firms have a sign on the door. You can smell bread
baking at a bread factory. But arts and cultural activities cut across traditional distinctions
between residence, employment, and retail uses—they happen in all three, and it is hard to
separate them. The West Queen West neighborhood had one of the highest concentrations
of arts workers of any neighborhood in Canada, but nobody could prove it in order to
show its relative importance to the city as a whole. The impact of new developments on
similarly significant biotech or finance clusters would without question figure in planning
decisions for their neighborhoods. For policy makers to similarly consider arts and culture
clusters, they need to know that such clusters are there. Hence we made maps showing
them.
Box 7.7 Big Box Reuse
The Lebanon-Laclede County Library in Lebanon, Mo., lives in a renovated Kmart building. The library
had been trying to expand for years before the plan to use the old Kmart site fell into place. The building is
now shared by the library, Maria’s cafe, and the Route 66 Museum—which is full of maps, road signs, and
other memorabilia from the historic highway. . . .
. . . The Spam Museum in downtown Austin, Minn., is home of Hormel, maker of the famous canned
meat product. The museum operates in a renovated Kmart building, which sat empty for several years after
the retailer moved to a bigger location on the edge of town. In 2000, the Hormel Corp. bought the store to
expand its headquarters less than two miles away. The company held a design competition for dibs on
renovating the space, and Paulsen Architects, a firm from Mankato, Minn., won. Half of the building
houses the Spam Museum; the other half, additional offices for Hormel.
The Spam Museum has helped revitalize this small, quiet meatpacking Minnesota community, which
now proudly proclaims itself “Spam Town USA.” More than 10,000 people travel to Austin every year to
visit the museum. Walking paths between the museum site and downtown Austin extend the flow of
visitors into the downtown business district.
. . . The Calvary Chapel in Pinellas Park, Fla., purchased an abandoned Wal-Mart building across the
street from its previous home. The deed specified that the structure could not be used by one of Wal-Mart’s
various competitors for several decades. But for the moment, at least, churches aren’t on that list. Many
former big-box stores have been reclaimed by civic institutions—a library, a courthouse—and by churches.
Before moving into this old Wal-Mart, the Calvary Chapel had made its home in an abandoned Winn-Dixie
grocery store across the highway. . . .
The Peddler’s Mall is a chain of flea markets started by Kentuckian John George . . . Currently, there are
18 Peddler’s Mall stores in operation, many of them in old Wal-Mart buildings. George says the ideal
scenario is when Wal-Mart moves right across the street, because its stores generate so much traffic. Often
people will stop in the Peddler’s Mall before going to Wal-Mart to see whether any of his vendors have
what they are looking for—at an even lower price. . . .
The Head Start Early Childhood Center of Hastings, Neb., makes its home in a renovated Kmart. The
Head Start lost its original building in a tornado in 1998 and continued operations in ad hoc classrooms and
basements around town before purchasing the old Kmart site. Deb Ross, the school’s director, drew up the
building plans herself. What was once the cargo bay of the Kmart is now a playground for students. . . .
Although big-box stores may appear to have an ephemeral, disposable quality, these structures rarely just
go away. They exert power over our communities long after the companies that built them have turned off
the lights. Integrating these unwieldy structures into the commercial or civic life of our cities and towns
requires ingenuity, but as the retail landscape of America continues to change, it is also becoming
increasingly imperative.
— Julia Christensen, “For Sale: 200,000-Square-Foot-Box” (2008)
Analyze both where people live and where they work. One major finding of the
report is that artists and cultural workers differ from the rest of the workforce in where
they live, but not so much in where they work. The difference is that they
disproportionately live (a) in the central city and (b) near one another. Their presence is a
key element in what makes the central city attractive and intriguing to others.
That they cluster together also suggests that they gain benefits from being near one
another. And this implies that a supportive scene can feed directly into their work. That
this is not a phenomenon unique to Toronto we demonstrated in chapter 4. Artists in an
arts-friendly scene generate significantly greater economic growth than do artists in a less
arts-friendly scene. This is a strong justification for urban policies designed to maintain a
strong link between artists and scenes, perhaps through subsidizing artist housing or
expanding the housing stock, so that artists and other low-income persons can afford to
live in gentrifying scenes. Consider options that work for your locality.
Link numbers and maps to people. While numbers and maps are important, in the end
the goal was to show how access to distinctive cultural scenes empowers people to
improve their lives. We thus included in the report short case studies, quasi-ethnographies,
that feature key scene makers. These illustrate how these individuals helped create
Toronto’s distinctive scenes that many others enjoy and benefit from, as well as how their
own work was enhanced by easy access to a scene. This takes us beyond dots and charts,
and animates the message with human interest. While the particular stories and scenes
would differ in different cities and neighborhoods, the goal of humanizing scene policy
does not.
Offer language and logic for explaining why scenes matter. Maps and trend lines
show what is happening and provide important policy tools. But these take on more
meaning if policy makers have a language and logic to explain to themselves and others
why these matter. Hence the main thrust of chapter 3 of the report, “The Economic
Importance of Cultural Scenes.”
This chapter outlines several mechanisms through which strong scenes can generate
prosperity. For instance, on the consumption side, they can keep spending local that might
otherwise leave town (e.g., through “staycations” rather than vacations), cultivate nascent
interests and hence expand local participation, draw new residents, retain existing ones,
and more. On the production side, the right scene can provide supportive yet critical
networks crucial to experimental and risky work, place branding, technique- and ideasharing opportunities, and more. These are clear and simple processes; enumerating them
explicitly can encourage decisions with a firmer understanding of why and how these
processes should work.
Avoid one-size-fits-all recommendations. The report’s specific policy
recommendations lay out multiple possibilities for different situations. Some examples
include publicizing relatively under-the-radar scenes, connecting them better to one
another, and exploring cultural district designations. In addition, we stress that sometimes
“hands off!” is the best policy, as a scene can thrive on organic, spontaneous growth that
too much intervention can spoil. More important than the specifics is to expand the
horizon of what is possible when plans and policies are formulated.
Keep the energy going after a plan or policy is written. Officials who work in
complex organizations like city government know that writing a memo or report is only
the first step of the game. One has to keep at it, for months or years.
Getting a hearing at related agencies is crucial: the report made its way to the planning
department and the culture department, for instance, where their staff attended and
discussed it. Elected officials need to be engaged, especially the leaders of key
committees. Maps can be tailored to specific political wards but also designed to show the
general importance of vibrant cultural scenes to the city as a whole. The report’s maps
were warmly received even by city councilors without reputations for being stalwart
friends of the arts. Also important is to integrate ideas emerging from different reports into
a coherent general cultural policy message. From the Ground Up was featured in the city’s
new culture plan, which explicitly mentions the importance of scenes as a cultural
development goal with the city’s general commitment to creative place making.
The challenge here is to convey to others the energy that lies behind the final product.
City staff obviously have to take the lead in keeping a new policy tool or idea on the
bureaucratic agenda. But they help themselves by inviting their collaborators to city
meetings, and their collaborators can help by accepting the invitation. Getting the whole
group together, or at least a few members, shows an ongoing commitment to the ideas. It
also models to others the types of innovative collaboration that are worth pursuing further.
Simply getting the word out can make a big difference. Staff think about and perceive
their options in a different light—maybe somebody notices something about a
development proposal she would not have without having discussed the ideas, or is
inspired to pick up the phone to call a colleague in a different department about an issue
that she would not have otherwise seen as an opportunity for collaboration. These
informal results are “policy outcomes” that are also important, even if they do not make
their way into official plans or legislation.
Principles of Scenes Policy
A few simple principles help synthesize the main lines of a scene-based urban policy. The
most general principle is that understanding policy options means linking macro-global
trends in the economy and society to local context and political culture. Here’s how to do
so:
1. Consider the specific people, actors, groups who have a stake in policy issues relevant to scenes—cultural
affairs departments, cultural industries, nonprofit cultural organizations, activist groups, citizens, mayors,
artists, residents, youth, and so on. The particular constellation of actors will vary in different places, as will
their influence and resources. Success depends on bringing these groups together and aligning their
interests.
2. Be flexible, and promote flexibility in others. Remember that many new projects fail; put your eggs in
multiple baskets. Consider not just one project like a library, museum, gallery, or restaurant, but how to
combine many such amenities, private and public, to build an attractive scene.
3. Measure success by empowerment. Making a difference often means enabling more people to make a
difference for themselves. Consider what scenes best allow citizens to do and be the best version of
themselves. Standard measures are when people move to or away from a neighborhood, or it rises in
average education or income, but watch for more subtle processes too, like turnout at local meetings,
neighborhood cleanups, and festivals, or how local folks talk about these issues. Be sensitive to competing
criteria and how to respond variously—for some folks not raising neighborhood rent or income is a goal.
4. Achieving specific goals is important but so is building organizational capacity. Think about policy
outcomes not only in terms of which groups get what they want. We may not get everything we want today,
but we can change how the game is played, add new players, and help build new policy tools and ideas
more deeply into policy-making mentalities/institutions. This is key for new groups and scenes, like artists
or youth groups.
5. Talk to citizens, and listen to their concerns. Don’t say “if we build it, they will come.” Instead ask what
people want first, and assess nearby projects. Then ask the planners and architects to include these concerns
in new land use and building. Ask them to comment on how individual projects may affect area scenes.
These points are neither radical nor new. But their very simplicity can often be what
makes them difficult to stick to, especially when there is usually some proposal for some
new universal engine of urban prosperity making news. Yes, look far and wide for new
best practices. But the point of doing so is to learn more about yourself, to get a clearer
picture of what scenes you have and what might be done to build on that distinct character.
The concepts and techniques in this book provide a way to do so: to situate your local
scene in the context of many others; define more precisely what scenes are here and how
their key dimensions work; to learn how much is shared with others, how much is not; and
to bring some data to bear on the question of how important these similarities and
differences are in shaping your community’s future. These activities have encouraged
innovative policies and outcomes in other places and could do so in your area too.
8
The Science of Scenes
With Christopher M. Graziul
Many scientific endeavors rely on highly specialized equipment to probe indirect evidence
supporting or disconfirming a theory, and so it goes with Scenescapes. The styles of life
we seek to uncover are amorphous, ephemeral, and defy traditional measurement. They
are embedded in a built environment whose components are saturated with meaning.
That the physical structures of amenities are saturated with meaning poses classic
methodological challenges—quantitative, qualitative, philosophical, or otherwise—for
their interpreters. Thus Jürgen Habermas points out, during his account of how
coffeehouses helped create a public civil sphere in eighteenth-century England, that cafes
were not culturally significant because they served coffee. Yet they still served coffee.
Conversely, not every gentleman of the time who frequented a coffeehouse did so to
participate in a new form of critical discourse.
Similarly, scenes require the action and energy of human beings to create and support
the meanings they offer. This implies that scenes can never be measured completely
through any method, let alone by counting the amenities in a community. The “signal” that
would indicate the existence of a particular scene at least partially resides in community
members (their traits, tastes, and activities) and involves a wider audience attaching
certain meanings to places within the community. We therefore primarily deal with
indirect evidence of an abstract and emergent cultural phenomenon. In other words, our
main data, local amenities, are not constitutive of scenes but, through the science of
scenes, become useful indicators of the qualities that constitute scenes.
One helpful way to understand the transformative process that allows us to go from
amenities to scenes is to consider the example of experimental particle physics.1 The goal
of a science of scenes is to detect the constituent cultural components of a location by
observing amenities that have manifold meanings. Particle accelerators are a response to
similar challenges faced by physicists. Sometimes the existence of certain unobservable
constituent particles can only be inferred by observing how larger, more complex particles
interact with one another. Thus many efforts to discover new and exotic particles involve
laboriously confirming that a certain soup of particles could only have come about
because of the predicted properties of a seemingly invisible ingredient. In the same way,
scenes analysis makes inferences about things we cannot see directly (glamour, selfexpression, formality, charisma) by observing things that we can see—in this case,
amenities.
Beyond facing similar epistemological issues, the science of scenes also shares a
surprising number of practical problems with the science of particle physics. Both seek to
confirm theoretical predictions by constructing highly specialized tools for collecting
indirect evidence. Both must discriminate between “noise” and “signal,” between
irrelevant or meaningless data and meaningful data within this indirect evidence. And to
do so, again like particle physicists, we start with a very concrete theory of “what is out
there” and proceed as if the world truly operates that way, searching for the best indirect
evidence we can find that enables us to confirm or disconfirm our theory.
Accordingly, a major methodological challenge for scenes analysis is to develop ways
to turn our main indirect indicators—amenities—into measures of scenes. The physics
analogy continues: Just as researchers employ multiple detectors to jointly observe the
properties of a particle (e.g., trajectory and electrical charge), we create a set of measures
for jointly observing the properties of a scene (e.g., transgressiveness and traditionalism).
Just as researchers repeatedly perform the same collisions to statistically test the
likelihood that the soup of particles they observe implies the existence of unobservable
particles, we employ data on tens of thousands of locations to statistically test the
likelihood that the amenities we observe imply the existence of particular scenes.
And just as there is a Standard Model of particle physics, we have a “standard model”
of scenes. This model describes the constituent units of scenes, which we call dimensions,
and allows us to theorize how scenes ought to relate to more traditional social science
variables, like income or education. A science of scenes thus needs to demonstrate how
the properties of a location’s scene, indicated by its amenities, relate in theoretically
consistent ways to other more tangible features of the community.
However, social scientists face methodological challenges that physical scientists do
not. Our hypothesized relationships cannot be reduced to a series of syllogisms, and the
novelty of our approach suggests that a lack of a relationship may reflect a poorly
constructed measure instead of meaningful empirical research. This chapter is accordingly
about providing insight into the thinking and decisions that went on—and are still going
on—“behind the scenes” of Scenescapes, which is by no means the final word on the
topic. This is a science of scenes as an ongoing dialogue between theory and observation.
We are not so arrogant as to believe that the 15 dimensions we pose are the only ones, or
even the best; they are provisional and pragmatic interpretations from past related work.
Our goal here is to point out to readers, especially those with doubts about analytic
decisions in previous chapters, the utility of the underlying techniques such that others can
adjust our concepts and pursue their own ways to build meaning using the types of data
we utilize.
Goals of the chapter. How do we get from (a) information about amenities like public
parks, bookstores, and tattoo parlors to (b) quantitatively analyzing how, for instance, selfexpressive scenes relate to economic growth? The line from (a) to (b) is not direct or
immediately obvious, and accordingly, Scenescapes often opts to provide relatively
intuitive and accessible arguments about this process rather than extensive details that may
appear esoteric to most readers. This chapter provides technical details that more
quantitatively oriented readers (like professional social scientists) would naturally want to
know.
One major aim of the chapter is thus to describe and justify our methods for quantifying
the presence of scenes and how they relate to urban development. We start with an
overview of the national database of local amenities we compiled, one of the most
extensive of its kind to date. Next we describe how we transform these data from
measures of what is there (amenities data) to measures of what that means (the
performance score measures of scene dimensions like self-expression or neighborliness).
We then discuss our standard methodological approach for jointly analyzing how scenes
and other more traditional data relate to urban development. To do this, we review
multiple ways to model spatial context and apply these techniques to an illustrative result
from chapter 5 (that between 1990 and 2000, 25- to 34-year-olds increased in
transgressive but not self-expressive scenes).
This discussion of modeling context is important in a number of ways. It helps to
validate the robustness of the standard methods in Scenescapes by showing that more
sophisticated techniques produce results that are generally consistent with those generated
using a simpler approach. Perhaps more importantly, it joins scenes analysis with more
recent research involving spatial and contextual analysis. These research efforts have
produced new tools for explicitly analyzing the role of context in myriad social
processes.2 Indeed, if in the past many social scientists turned to qualitative methods (in
part) because of dissatisfaction with the intellectual simplifications inherent in basic
quantitative techniques—descriptive maps, frequency distributions, cross tabulations, or
linear regression analysis—newer methods permit crucial ideas from qualitative work
(like context) to be more directly modeled quantitatively. These novel approaches allow us
to explicitly analyze how the situations in which life unfolds affect its meaning and
course, and we are able to do so across far larger geographic areas than ever before.
Even though methods have advanced rapidly in recent years, less progress has been
made to join them with concepts designed to bring some of the subtlety of ethnography
and qualitative research into large-scale statistical analyses. Realizing this potential is one
of the major methodological goals of the scenes approach, as we have stressed throughout
Scenescapes. In chapter 3, we laid out some of the intuitive logic for how proximity alters
performance, that is, how when some scenes are near one another, this spatial
configuration may shift their meanings and impacts. And later chapters explicitly analyzed
contextual effects, as in the chapter 4 discussion of the economic impacts of Bohemian zip
codes in communitarian or urbane counties, and the chapter 6 discussion of how affluent
counties are less likely to be Republican when they have a transgressive scene. Here we
extend these ideas about context and incorporate more advanced techniques, showing how
scenes concepts and data can create more substantive meaning when combined with the
modeling of spatial effects.
Another aim of the chapter is to review a series of approaches to the analysis of scenes
that we explored but ultimately did not report in the main analytical chapters. We begin
with a discussion of causality and the implications of employing scenes as an outcome
rather than a predictor. We end with a review of ongoing international scenes research.
The intent here is to show how we grappled with various analytic questions and to suggest
some of the many possible directions for future research employing the scenes paradigm.
From Theory to Data
Many of our scenes concepts, data, and methods are new, but they have important
precedents. One important inspiration is recent work seeking to develop a “cultural
sociology” in general and an “urban culturalist perspective” in particular.3 This research
has tacitly reenergized an idea shared by classic figures such as Weber, Simmel,
Durkheim, and James: the idea to bring seemingly transcendental values down to earth
and to see their tangible role in social life.
Thus rather than treating cultural meaning as the necessary condition of social
integration, or strategic tool kits,4 many look to the social currency of meanings already
embedded in concrete places and practices5—in trees, rivers, parks, street corners,
neighborhoods, record shops, sidewalks, baseball parks, blues clubs, bumper stickers, and
so on.6 Others have developed proposals for how to measure “meaning structures” and
investigate their correlations with, for instance, leadership and occupational patterns.7
A related inspiration includes writings more explicitly devoted to studying phenomena
under the heading of “scene.” While the concept has been loosely used by art and music
critics for decades, academic researchers have focused on “scenes” as a means to trace the
role of national theaters and lifestyle communities in modernization processes, as niches
for urban belonging in the metropolis that do not require nostalgia for the premodern
village (Straw 2001), and as links to “youth” with respect to a specific phase of the life
course.8 Bennett and Peterson (2004) compile descriptions of various music scenes,
dividing them into local, global, and virtual. Lena and Peterson (2008) treat “scenes” as
one phase in the life course of music genres, as they grow from avant-garde to scenebased to industrial to nostalgic communities. And Haunss and Leach (2007) and
Lichterman and Eliasoph (2014) highlight how scenes sometimes animate social
movements.
It would be a mistake to call this work a “literature” in the sense of the product of an
interconnected research community cumulatively pursuing a scientific program. Most
ignore the others and they have largely emerged independently. Still, our review of these
works (among others) helped formulate our conception of scenes as the meanings
expressed by the people and practices in a place (Haunss and Leach’s 2007 review
produced a similar result). At the same time, our multidimensional theory of scenes
incorporates some of the main themes stressed by others, such as exhibitionism and
transgression (Blum 2003), local authenticity (Zukin 2010; Grazian 2003), and more (as
described in chapter 2). But we sought to develop a more comprehensive and integrated
analytical framework.
Beyond this theoretical contribution, a primary goal of Scenescapes is to meld cultural
theories with data to make qualitative meanings embedded in places not just observable
but, in an albeit limited way, quantifiable. Much past effort has been devoted to develop
methods for examining and measuring other core aspects of cities and communities—how
big they are, how much they produce, how many they employ. Very little work has sought
to create measures of their expressive organization, their scenescape.
Finally, both conceptually and methodologically, from the outset we sought to develop
an analytical perspective and operational measures that could travel globally. Taking
seriously how global we are is a relatively new challenge in general, and asking how to
build this globalism into our core concepts and thinking is even newer. This wide-ranging
scope was facilitated by working with the ideas, data, and people who developed the
Fiscal Austerity and Urban Innovation Project over the previous quarter century into one
of the most comprehensively international projects in the social sciences.9
While recognizing these foundations, we still had to chart much new conceptual and
methodological territory. The conceptual syntheses in the above chapters emerge from
Daniel Silver’s training at the University of Chicago’s Committee on Social Thought,
where dialogue with Aristotle, Hegel, and Baudelaire is a daily staple. But he found new
specific ways to join these with street conversations and regression coefficients. Terry
Clark’s past work is more urban and classically sociological, although he moved toward
scenes ideas via art school, the Frankfurt School, five years in Paris, and biking Chicago
neighborhoods. We joined in an effort to build a new way to incorporate cultural ideas into
sociological discussions, which often downplay their significance.
To do so, we (1) compiled a nationwide database with hundreds of types of amenities,
supplemented by citizen surveys and other information about neighborhoods. It is largely
the product of some 15 University of Chicago students working hard over ten years with,
alas, continuous turnover as graduations and other diversions intervened. We then (2)
explored many conceptual approaches in the course of our research, continuously building
our own analytical framework over nearly a decade. Next we (3) “translated” much of our
data into measures of the 15 dimensions of theatricality, authenticity, and legitimacy we
present here. After much exploration and experimentation, we found performance scores
to be the most theoretically and methodologically compelling measures of scenes.
Clemente Navarro was our constant companion in extending these tools, and Lawrence
Rothfield was a key contributor in developing our initial conceptualization of scenes.
Throughout we have (4) been in dialogue and debate with leading theorists, especially
in Los Angeles, Paris, and New York, about the nature of the “New Chicago School” and
how our theories can address the most challenging urban questions nationally and
globally.10 We have (5) continually worked with many students and colleagues from
around the world, consulting with persons from Beijing to Seoul to Paris to Seville and
beyond who were simultaneously developing similar projects elsewhere. For instance, a
Seoul Development Institute report and Can Tocqueville Karaoke? centrally address how
Western urban theories need modification to understand Asia, especially Tocqueville’s
ideas about democratic consensus and recent claims about the role of Bohemia in spurring
urban growth.11 Yet we also (6) worked with others (especially some 75 students writing
papers on these and related themes) on specific neighborhoods studies, often in Chicago,
to explore specific themes like glamour, Bohemia, blue-collar Bobo, and the like, which
have frequented the pages of Scenescapes. This cross-fertilization has yielded a large and
growing international body of research applying and extending the scenes perspective.
Some project websites include scenescapes.weebly.com and scenes.en-linea.eu/en/.
Box 8.1 International Scenes Research: A Brief Overview
Scenescapes is emphatically a part of a broader scene that includes researchers pursuing similar questions
in many countries. Here is a small sample of some of that work. Links to these and more can be found at
scenescapes.weebly.com.
General Statements
Navarro, Clemente J. Las dimensiones culturales de la ciudad: Creatividad, entretenimiento y
difusión cultural en las ciudades española. Madrid: Los Libros de la Catarata, 2012.
Silver, Daniel, and Terry Nichols Clark. “The Power of Scenes: Quantities of Amenities and
Qualities of Places.” Cultural Studies 29, no. 3 (2015): 425–49.
Spain
Spanish project website, with links to many books and articles, as well as step-by-step explanations
of how to construct scenes measures, in English and Spanish: http://riemann.upo.es/cspl/scenes/.
France
Sawyer, Stephen, ed. Une cartographie culturelle de Paris-Métropole: Les Ambiances du ParisMétropole. Paris: Rapport a la Mairie de Paris, 2011.
Korea
Byun, Miree, Wonho Jang, Terry Clark, and Jong Youl Lee. Seoul Scenes’ and Its Use for Space
Characterization. Seoul: Seoul Development Institute, 2011.
Poland
Klekotko, Marta, and Clemente Navarro, eds. Wymiary kulturowe polskich miast i miasteczek.
Cracow: Jagiellonian University Press, forthcoming. [In Polish. English translation in
preparation.]
China
Di Wu. The Research on Urban Residential Choice and Housing Price’s Spatial Difference in
China: Based on the Theory of Scenes. [In Chinese.] Beijing: Economy & Management
Publishing House. 2013.
International and Comparative
Jang, Wonho, Terry Clark, and Miree Byun. Scenes Dynamics in Global Cities: Seoul, Tokyo, and
Chicago. Seoul: Seoul Development Institute, 2011.
These multiple contacts have (7) made us both more cosmopolitan and more conscious
of the contexts, and the limits, of our analytical enterprise. Most theories propose 2 or 3
main types; we use 15! These emerged from challenging ourselves to build a theory
general enough to cover the world while incorporating enough subtlety to dialogue with
the street-smart participants elaborating on the great traditions of Chicago urban research.
Some 15 of us (mainly University of Chicago students and visiting scholars) would
generally meet for two hours weekly, joining these many overlapping activities and talking
through each key research decision. Scenescapes is emphatically a team effort, and while
most data in this volume are for the United States and Canada, they are interpreted in a
manner informed by the gaze of many other scenes. When we failed, others corrected us,
repeatedly. We started over many times and will likely do so again.
Why Have a National Database of Local Indicators?
This section reviews the main considerations we took into account when searching for
suitable scenes data, and then provides a description of the data we ultimately used. The
sharpest difference from past work is our inclusion of hundreds of indicators to capture the
wide range of cultural dimensions in our theory of scenes. Our decision to explore this
seldom-used wealth of data is based on our goal of capturing cultural context as a holistic
experience incorporating the built environment.
Beyond atomism. Economists (many at Chicago) have pioneered in theorizing
amenities, and we build on their legacy.12 But they largely did so by focusing on just one
or a few amenities, which amounts to assuming a vacuum around any single amenity. That
is, economists generally reason atomistically and ignore context via the ceteris paribus
assumption. Thus, a perfectly reasonable way to study rent prices in urban settings, based
on this assumption, is to add January temperature to a standard set of variables known to
predict rent in order to estimate the dollar value of January temperature. This is termed
hedonic price analysis. One could do the same for restaurants or other amenities, and
many have (e.g., Albouy, Leibovici, and Warman 2013).
However, this atomistic approach neglects to consider the fact that patrons of a
restaurant next to a tattoo parlor will likely differ substantially from patrons of another
restaurant next to an opera, with quite distinct implications for residential and economic
growth.13 Thus, we try to capture what makes locations different from one another by
including many lifestyle indicators that jointly create the context, giving meaning to the
many specific amenities in that scene. The scene in this respect is an emergent property
based on its combinatorial logic of adjacency to multiple individual amenities. This holism
contrasts with the atomism of most past amenities work.
What Would an Ideal Scenes Data Set Be Like?
Our methodological goal in building the scenes database is to join the subtlety of meaning
found in strong ethnographic studies with the wide-scale comparative analysis possible in
quantitative research. To achieve this end, we have had to juggle several important yet
competing priorities when searching for data sets. Clearly no source is perfect in all these
respects, but we list them as our guides, our selection criteria, albeit imperfectly
implemented.
An ideal scenes data set would possess several qualities. First, the data should be
geographically comprehensive. The data should be nationwide and the product of
consistent methods of collection across the country. When we move to international work,
we seek to retain such comparability, and we rely on experts (especially national and
international statistical agencies) whose job is to assemble and adjust raw local items to
make them more comparable. Such data provide maximal comparability of regions with
widely varying cultural and historical trajectories, preventing, ideally, these unique
features from biasing results. Further, since we make no a priori distinction between urban
and rural scenes, we eschew categorical distinctions between these two settings and prefer
data that represent a continuous sampling of geographies from the largest and most
densely populated to the smallest and least densely populated. Barring this
comprehensiveness, a data set should, at the very least, provide information for a large
percentage of the population by area—not just the largest metropolitan areas, but as much
of the country as possible.
Second, because scenes are largely submetropolitan phenomena, the data should
possess a high degree of spatial resolution. Ideally, these data would attach street
addresses (i.e., points with latitude and longitude coordinates) to each data item and
include information on who frequents these places. If these details are not available, our
preferred geographic unit of analysis is the zip code or its equivalent, permitting analysis
of some neighborhood-level effects by inferring that local patrons exist for the amenities
in these small areas, though even more spatially refined data is preferable and will
hopefully become available in the future.14 Less spatially refined data (e.g., cities,
counties, metro areas, and states) provide useful but more limited insight into the
scenescape by masking the internal variation an average resident would experience while
moving through these larger areas (cities, counties, etc.).
Third, the data should differentiate amenities as much as possible. Knowing that there is
1 business or 50 businesses in a given zip code says little about what that business does
and what scenes are evinced by its presence. Knowing that a business is a retail
establishment adds a little; knowing that it is a restaurant says more; knowing that it is a
West Indian restaurant says much more still. Similarly, it is important to know what else is
nearby. Is our restaurant in a West Indian enclave? Or is it in a cosmopolitan scene, next
door to sushi, Thai food, and a French bistro? Do residents there go out frequently or are
they homebodies? Do they enjoy trying new things or fear change? (Self-reports on these
types of activities and attitudes are in the DDB survey we also use.) Finally, this
differentiation should also include the cultural content. Data on five different kinds of gas
stations are far less informative than data on five kinds of ethnic restaurants.
Fourth, an amenity should ideally be spatially invariant in its potential availability and
typical practices. Local users should be able to reveal their preferences by patronizing a
Thai restaurant, but if citizens prefer catfish restaurants, the local market should not
prohibit a catfish restaurant from emerging. Thus in some cross-national work where
market entry is more constrained (e.g., beef in India), the regulations and other factors that
affect market entry by new firms should be incorporated into the analysis. Further,
independent of how its meaning is attenuated by (or contributes to) its surrounding
environment to constitute its scene, an amenity’s label, such as “Thai restaurants” in a
business directory, should consistently refer to a similar set of practices, such as making
and eating Thai food rather than pizza. That is, category labels should be functionally
equivalent in their referents. Standardized items such as Starbucks and McDonalds meet
this criterion relatively straightforwardly, though even here the issue is complex; less
standardized items such as cultural centers (which offer diverse activities) and restaurants
(which differ by cuisine and price) are more difficult.15
Finally, the data should permit analysis of trends over time. This is important for
multiple, sometimes subtle reasons. First, causal direction is a prime concern when
discussing the relationship between scenes and major indicators of economic growth.
Second, the stability or impermanence of scenes over time is an important phenomenon
worth investigating in its own right. Similarly, a data set of any substantial size tends to
have “noise” within it, and being able to average over multiple years can reduce this issue
when, for instance, a small town or neighborhood has many coffee shops that open and
close within a few years. Finally, time series analysis of scenes data can provide important
insight into how economic recessions, neighborhood population composition,
gentrification, and so forth, may influence the cultural life of regions, as well as whether
certain types of scenes are more or less resilient to these changes.
Scenes Data Sources
A data source that perfectly conforms to these ideals is utopian. So we did what most
social researchers do: we used the best of what was available to us, looking for errors and
irregularities and ways to assess how much these discrepancies bias our results.
Our scenes database has two main sources: (1) the US Census Bureau’s Zip Code
Business Patterns (BIZZIP) from 2001 and (2) an original data set using online business
directories often known as yellow pages (YP). We supplemented these two sources with
many others, such as the DDB Needham Lifestyle Survey, the Urban Institute’s Unified
Database of Arts Organizations, arts organizations’ professional directories, and more.
After exploring many possibilities, we decided that BIZZIP and YP best fit our criteria for
capturing the holistic scenescape in its richness and subtlety. BIZZIP and YP both have
distinct benefits and drawbacks, though each provides critical indirect evidence of scenes.
Their joint use, along with supplements, produces a more illuminating picture than any
one source alone.
Consider briefly the strengths and weaknesses of each, starting with BIZZIP. BIZZIP
utilizes a system of classification known as the North American Industry Classification
System (NAICS). This data product provides extensive information on commercial and
noncommercial entities—for example, theater companies and musical groups, promoters
of performing arts, museums, independent artists, and even human rights organizations,
environmental groups, and religious organizations. BIZZIP is also not just a sample; it
enumerates the entire population. Its universe is all US zip codes, and its data are drawn
from multiple federally collected data sources—primarily the continuously updated
Business Register and the periodically undertaken Economic Census.16 As an annual
survey of businesses, BIZZIP permits analysis of amenity mix changes over time.
Only a handful of analysts have made use of the BIZZIP data; most economists use a
geographically aggregated version, County Business Patterns.17 Use of BIZZIP in social
scientific research has been rare since it has not been publicized, and because of the
difficulties posed by utilizing hundreds of indicators in a theoretically consistent and
meaningful way, not to mention the technical challenges in compiling the raw data into an
analyzable format. Scenescapes is thus also an attempt to bring this rich source of data to
the attention of more potential users. Many countries report similar data, some in nearidentical format.
Yet BIZZIP clearly has its limits. Most information concerns more formal organizations
(e.g., businesses and nonprofits, as opposed to public parks) and is classified more from a
production and bureaucratic perspective than from a consumption perspective. And while
it is good to know how many restaurants are in an area, for instance, BIZZIP does not
report what kinds of restaurants are present; BIZZIP simply reports the number of
restaurants in each zip code. Do they serve Italian, Korean, or Lebanese food? Is the
restaurant local or part of a national or regional chain? To gain access to these kinds of
cultural differentiations, we employed a commercial program to systematically download
hundreds of categories from online yellow pages sources to create our second scenes data
source, YP. We used similar procedures with our scenes collaborators in other countries.
After reviewing several possible providers, we opted for superpages.com, because its
geographic coverage was the most extensive and its categorization scheme the most
consistent and fine grained, especially for items with rich cultural content.18 YP thus
provides a much higher degree of specificity than BIZZIP in terms of categories (Chinese
restaurants are differentiated from Mongolian restaurants, Baptist churches from Catholic
churches, etc.). YP is also more geographically specific than BIZZIP: data are available by
street address, thus providing points in space for Geographic Information Systems (GIS)
software. However, for Scenescapes we generally aggregated the total number in each YP
category to the zip code level, producing a data set similar to BIZZIP. Clearly, emerging
sources like Google’s business directories and street-view images or Yelp’s reviews
provide significant methodological opportunities.
The yellow pages also have their limits. Unlike BIZZIP, the YP data are not collected
with completeness as a goal. Either by accident or by design (e.g., by omitting businesses
that do not advertise or have a business phone, for instance), it is more likely to miss
establishments. For instance, our BIZZIP amenities cover almost 4,000 more zip codes
than YP amenities do (out of the 42,192 US Postal Service zip codes, there are 35,675
with at least one BIZZIP amenity versus 31,874 with at least one YP amenity). Moreover,
there is a documented rationale for BIZZIP’s classification system, while no such
information is available for YP. YP expresses a market logic rather than
government/bureaucratic logic: individual businesses usually select their categories from a
preset list, meaning that the categorizations reflect proprietors’ understandings of the
nature of their businesses and intended consumers, rather than a social scientist’s
understanding. Moreover, so far we have collected yellow pages data for only one time
point, 2006 in the United States and 2009 in Canada. Longitudinal data are hard to acquire
as past years’ data are not saved or published electronically.
We supplemented YP and BIZZIP with other sources, most notably the DDB Needham
Lifestyle Survey (DDB). DDB is a nationally representative survey of American
consumers. Since individuals’ attitudes and behaviors are important elements of a scene,
we often look to DDB data (which we typically reported in the notes) to examine lifestyle
differences among groups (like postgraduates versus holders of bachelor’s degrees) or to
investigate characteristics of individuals who live within certain scenes (such as the
political attitudes of people who live in Blue Blood counties). More details on the DDB
are in the online appendix (www.press.uchicago.edu/sites/scenescapes).
We also investigated many other sources. Using national surveys, IRS returns, and other
sources, the Urban Institute’s Unified Database of Arts Organizations (UDAO) provides
useful national information about local concentrations of arts and cultural organizations.
These data items are often highly specific by discipline (e.g., modern dance, new music,
ethnic dance, puppetry, ceramics) and organizational goals (e.g., ethnic and cultural
awareness, community service, media dissemination). In addition, we searched for and
selectively employed information from specialized organizations, such as the Federation
of Genealogy Societies directory, Nielsen BookScan book sales databases, the Theater
Communications Group registry of roughly 700 theaters classified according to 24 special
interests (e.g., experimental, Asian American, African American, Native American,
puppetry, musicals), music venue information from the Pollstar Talent Buyer Directory
(which categorizes venues by size and type), musical activities from myspace.com (which
categorizes bands by genres),19 and library usage data from the American Library
Association. Even if we do not discuss them systematically, they inform the results we do
report, as we have explored them in many unreported analyses (such as checking BIZZIP
and YP against them for consistency), and we make them available to other researchers on
request.
More detailed summaries of specific amenities are in chapter 3. Table 8.1 provides basic
descriptive statistics for our main scenes indicators. Other variables and the main amenity
types in our analyses are detailed in the online appendix.
Table 8.1. Descriptive statistics for main US scenes data sources
Zip Code Business Patterns (BIZZIP)
Yellow pages (YP)
143
377
Mean
53
53
Median
12
14
Total
1,904,400
1,678,320
Mean
18
22
Median
8
10
Mode
1
1
35,675
31,874
Categories of amenities
Amenities per zip code
Types of amenities per zip code
No. of zip codes with data
Note: This table summarizes the amenities data from our two main data sources, YP and BIZZIP. “Amenities per zip
code” refers to the number of amenities of any kind in a zip code. “Types of Amenities per zip code” refers to the
number of different amenity categories (e.g., Thai restaurants and pizza restaurants) in a zip code.
To our knowledge, analysts have never before generated such a massive and
comprehensive database of amenities and other indicators of the culture of places. It took
us many years and is still growing, especially internationally with collaborators from
Canada to China, France to Korea (reviewed below). This database provides an
unprecedented opportunity both to understand the range of cultural experiences offered
across neighborhoods, cities, and regions and to assess the extent to which scenes either
share or help define the fortunes and fates of cities. Many data are available to others.
Measuring Scenes
Our amenities database was developed to provide a rich repository of information about
the range of experiences and practices on offer in every US zip code. With over 500 types
of amenities and nearly four million data points covering some 36,000 US zip codes from
YP and BIZZIP alone, it provides a broad sample of cultural meaning. As digitization and
computing power continue to advance, more opportunities for more data continue to
emerge, which can enhance and deepen insights from these measures of the scenescape.
More importantly, given our theory of scenes, simple counts of amenities like
restaurants do not yet tell us what the scene says about how one is supposed to be
theatrical, authentic, or legitimate. For this, we need a method for translating amenity
counts into measures of the 15 dimensions of theatricality, authenticity, and legitimacy
outlined in chapter 2, allowing us to detect interrelations among scenes and other
phenomena (economic, residential, political, etc.). The “performance score” featured
throughout Scenescapes is the main measure we settled on. Chapter 3 describes the
performance scores and how we calculate them in intuitive terms; here we focus more on
assumptions and methods guiding their construction. The aim is to demystify our
techniques for measuring scenes, beginning with how meaning is systematically attached
to each amenity to produce a “standard model” of scenes, continuing on to describe how
this meaning is quantitatively aggregated from a count of amenities to produce a single
number, and ending with a discussion of composite measures based on performance
scores.
Coding Amenities
A central feature of our efforts to translate what is there to what it means is the question of
how to accurately capture the scenic characteristics attached to a wide range of amenities.
Particle physicists have it easy by comparison: the Standard Model of particle physics
does not change based on what the physical world means to particles. Yet the “standard
model” of scenes certainly can (and does) change based on how people interpret their
environments. A key step in the science of scenes is therefore accurately capturing typical
interpretations of amenities in terms of the scenes dimensions they evince, somewhat in
the classical mode of Weber’s ideal types, though less as unitary constructs and more as
components that can be synergistically combined in multiple ways. Our approach is to use
a standardized coding system for classifying an amenity in terms of the 15 dimensions
outlined in chapter 2.
The process of attaching scenic meaning to our amenities represents a simultaneously
ontological and epistemological action. By recording what are ostensibly the nominal
scenic characteristics of a physical structure, we treat scenes as real and take the position
that we make scenes real by surveying the meaning associated with these physical
structures. The point is not small or tautological. The symbolic meaning of identically
labeled amenities will likely differ elsewhere. For instance, in Canada maple syrup camps
may express the kind of nationalism captured in our state authenticity dimension in a way
that they would not in the United States. This kind of variability justifies reliance on
knowledgeable informants to construct our empirical measures of scenes.
The informant method we utilize is not new or as sophisticated as ethnographic or large
N surveys.20 Rather, it is based on six informants (“coders”) who were considered to be
knowledgeable about the typical significance of the amenities in our database. The
decision to use so few informants was partly due to convenience and the exploratory
nature of the scenes project as a whole, but also because the threshold for recognizing the
meaning of these amenities is intentionally low—we are talking, after all, not about subtle
interpretations of complex texts or social interactions but rather whether adult
entertainment venues and opera houses affirm or reject transgressive theatricality, for
instance. “Intercoder reliability” is similarly employed in many social scientific studies,
often with the agreement of even fewer (trained) coders being taken as a strong sign of a
reasonably reliable measure. Robustness of our measures to small changes in coding or the
amenities included in their calculation is another way to check their reliability, as
described in the online appendix.
Our coders also needed to be able to speak the language of scenes. The scoring system
was the key for translating the information of amenities into the meaning of 15 scenes
dimensions. Chapter 3 provides intuitive examples of this system at work, which we
explain in a more technical way here. In this system, each amenity is assigned a score
from 1 to 5 on each of the 15 dimensions. Scores 4 and 5 indicate that the amenity (or
more specifically, through the practices it supports) affirms the dimension. Scores 1 and 2
indicate that the amenity (through the practices it supports) rejects the dimension. A score
of 3 indicates that the amenity’s practices are neutral on the dimension. The most
important decision is between a positive (4 or 5) or negative (1 or 2) score. We advised
coders to reserve extreme scores (5 and 1) for cases where an amenity’s label clearly and
directly indicates a given dimension as a core part of its meaning. The scores 4 and 2 were
for cases where the amenity might often or sometimes indicate a positive or negative
stance toward the dimension. Thus improv comedy might receive a 5 on self-expression,
but a generic art gallery only a 4.21
Applying the Scoring System to Data
A major goal in applying the scoring system to the data was for our coder-informants to
use common, clear, and standardized procedures in making their decisions. Coders were
asked to read drafts of important foundational documents for the research, which gave an
overview similar to chapter 2 on the scenes dimensions and the project. They were then
given our “Coder’s Handbook” which provided guidelines for assigning scores, specific
questions to ask in coding each dimension, and common pitfalls, as well as a series of
examples with rationales. Finally, they were presented with similar information in an
online tutorial. In essence, coders became trained experts in linking the 15 dimensions
with their potential indicators.
Coders then followed a standardized set of procedures for scoring each amenity. For
instance, they coded all items in the data set on traditional legitimacy rather than coding
all Chinese restaurants on all 15 dimensions at once. The intention was to focus attention
on one dimension at a time and utilize other amenities’ scores as a comparative tool for
difficult cases. Coders were then instructed to first ask themselves, in a specific question
tailored for each dimension, whether the value was positively affirmed by the activities
associated with the amenity. To determine whether the positives should be scored 4 or 5,
and the negatives 1 or 2, they were asked a follow-up question.
For example, to code the amenity category improv comedy clubs for the value selfexpressive legitimacy, the coder would read the question from “The Coder’s Handbook”:
“Is the amenity worthwhile because it expresses a commitment to the importance of
personal, creative, unique, novel expressions?” Improvised comedy clearly cultivates
spaces valorizing the legitimacy of individual self-expression, indicating that the amenity
would receive a positive score. To determine whether the appropriate score is 4 or 5, the
coder would then be asked whether “expressing the importance of creative, unique, novel
expressions is essential” to the amenity’s message. Again, the answer to this question is
yes; improv comedy—relative to other amenities—is deeply connected to expressing a
way of life in which authority is ultimately based on the unique expressions of
spontaneous selves. Therefore, the amenity would receive a score of 5.
If, however, the answer to the initial question were no, the coder would then be directed
to a negated form of the same question—for example, “Does the amenity express the
importance of blocking the creative, unique expression of self?” If the answer were no, the
amenity would be given a score of 3 on that value. If the answer to that question were yes,
then the coder would be asked a final question to determine whether to score 1 or 2.
Figure 8.1 represents this decision tree graphically for traditional legitimacy. And table 8.2
summarizes the questions coders asked as they scored each amenity along the 15
dimensions.
Figure 8.1
This figure shows the decision-making process coders employed in scoring each amenity on each of the scenes
dimensions using traditional legitimacy as an example.
Table 8.2. Coding questions
LEGITIMACY
The type of legitimacy promoted by a scene consists in the way it affirms or resists some basis of moral authority,
some standard of ethically right or wrong action.
Dimension Positive
Do the activities associated with [insert name of amenity here] assert that the right way to behave is
Traditional
according to heritage and/or the models provided by exemplary figures from the past?
Utilitarian
to calculatedly extract profit, especially for oneself, pursue disciplined, regular work, and/or delay
gratification?
Egalitarian
according to norms of universal, reciprocal respect for all persons and peoples?
Selfexpressive
in your own way, originally, uniquely, spontaneously, and/or creatively?
Charismatic
determined by the aura around a great leader, religious figure, or star?
THEATRICALITY
The type of theatricality promoted by a scene consists in the way it affirms or resists some style of appearance, some
way of seeing and being seen.
Dimension Positive
Do the activities associated with [insert name of amenity here] assert that the appropriate way to
display oneself is
Glamorous
as shining out, glittering, like gold, fashionably, sparkling?
Formal
according to ceremonial and/or ritualized, often codified standards of appearance or behavior?
Transgressive
as offending mainstream culture and values?
Neighborly
as warmly offering intimate, close, personal connection?
Exhibitionistic as a body on display, rather than for one’s personality or other individual, nonphysical attributes?
AUTHENTICITY
The type of authenticity promoted by a scene consists in the way it affirms or resists some way to be real or genuine
rather than fake or phony.
Dimension Positive
Do the activities associated with [insert name of amenity here] assert that being real rather than fake
comes from
Local
distinct local roots, a particular place with its own organic customs and practices?
Ethnic
ethnic roots, unadulterated by foreign traits?
Corporate
corporate brands, logos, culture, standardization?
State
citizenship, in being a member of a nation and participant in civic life?
Rational
sincere, pure, spontaneous exercise of the mind, regardless of time, nation, ethnicity, tribe, creed, or
color?
Note: This table shows questions coders asked themselves as they scored each amenity along each of the dimensions of
scenes.
The key to consistency was elaborating and detailing the coding guidelines, which we
did iteratively as we discovered different assumptions that led coders to different
decisions. As the work on coding progressed, all the coders met regularly to discuss
significant differences in coding as well as problems that emerged. This often led to
revisions in the coding manual and coding process. The coding lasted around a year, with
dozens of meetings that led to repeated revisions and clarifications, until we found relative
consensus. Where there was doubt or disagreement, instead of asking for the votes of
different coders, we encouraged open discussion and writing out the criteria for the
decision more explicitly. These discussions verified that all coders were on the same page
mentally, generating similar scores for similar reasons (see the helpful discussion of
similar issues by Abend, Petre, and Sauder [2013]).
The convergence process was continually monitored numerically through intercoder
correlations, for which we set a minimal reliability threshold (Pearson r) of 0.7 and
considered scores of 0.8 or above to be good. When we found items with r’s below 0.7, we
met and extensively discussed reasons for the differences, seeking to agree on as many
criteria as possible that were concrete and replicable in such a manner that others who
faced these same issues should reach the same basic conclusions. These discussions led to
revising and adding specific criteria for coding in our manual that in subsequent rounds
led to r’s greater than 0.7 among coders. Ultimately, we utilized coders’ average scores for
each dimension for each amenity, capturing remaining dissension that we provisionally
assume represents real differences in symbolic interpretation.
The foundation of the approach was iteratively building a high level of specificity into
“The Coder’s Handbook.” The creative part of the coding process was in the discussions,
where each coder reported reactions to each amenity. This led us to revise the handbook
until it had a level of precision that generated consistency among coders.
No doubt it is still possible to disagree with specific coding decisions.22 One might even
imagine utilizing subsets of coders from different regions of the United States and
applying their coding scheme to those regions, and the like. We do not insist that our
categories or coding decisions are the only valid ones. But we do hold that they conform
to the standards of measurement theory similar to most social science.23 Others may
organize the same data in different ways to see what happens, or posit the existence of
different dimensions of scenes. We repeated essentially similar methods in other national
contexts and performed several reliability and validity checks (see the online appendix).
An initial assessment of our coding efforts is their “face validity.” The question is how
effective are the resulting measures at supplying evidence for the presence of particular
scenes based on the total set of relations among the many amenities in our database.
Showing that they are rather effective was the methodological burden of chapter 3. A
further test of the coding comes through evaluating the “hypothesis validity” of our
measures based on that coding, to which we return below.
Computing Performance Scores
The result of our coding process is a matrix with rows for each amenity and columns for
the 15 scenes dimension scores that coders, on average, assigned to an amenity. The online
appendix summarizes the coding scores for all BIZZIP and YP amenities, respectively.
Table 8.3 shows an example of one row.
Table 8.3. Sample scene profile of one amenity, art dealers
NAICS d11i d12i d13i d14i d15i d21i d22i d23i d24i d25i d26i d31i d32i d33i d34i
453920
3
4
2.25
4
3
3
3.6
3
3.75
3
2
3
3
2.75
3
In table 8.3, 453920 is the US Census Bureau’s NAICS industry code for art dealers, an
amenity in the BIZZIP data set. The variables d11i, d12i, . . . d34i represent the 15 scenes
dimensions, with the cell numbers indicating the average coder score associated with each
dimension for art dealers. For example, coders judged that the existence of an art dealer
indicates more self-expression (d12i = 4) and less utilitarianism (d13i = 2.25).
This sort of matrix is the “standard model” of scenes, capturing how our amenities
should relate to each dimension according to the symbolic characteristics they embody.
Such matrices position each amenity within a complex of cultural meaning. Similarly
scored amenities indicate a similarly supportive or suppressive connection to each
dimension. Many researchers will recognize this matrix as similar to hypothesized factor
loadings associated with a confirmatory factor analysis. Typically the next step is to use
these factor loadings to construct the hypothesized covariance matrix, essentially
capturing which amenities should or should not colocate in the same geographic area,
based on their scenes characteristics. The final step would be to compare this covariance
matrix with a covariance matrix produced by examining the actual clustering of amenities
in our data. Too poor a fit between the two matrices would indicate that amenities do not
cluster together according to the “standard model” of scenes that coders created.
We have opted to not apply the typical fit criterion for confirmatory factor analysis for
two important reasons. First, we explicitly acknowledge that cultural meanings may not be
the primary driver for the creation and support of certain amenities. For instance,
economic incentives provided by localities (e.g., tax breaks or funding for public
recreation) will likely affect which amenities exist in a community. This is critical to
recognize for many of our analyses, since they are primarily about near-term
consequences or what happens given the presence of a certain scene, not why a certain
scene came into being in the first place.
Second, historic processes that far precede our data collection have almost certainly had
a path-dependent effect on the configuration of amenities in an area. Communities are
always changing, evolving, and refinding their pasts, and not only are our amenities data
largely cross-sectional at this time but most current data sources only extend back to the
early 1990s. Development processes that span multiple decades are simply not something
we can accurately measure. There is clearly “more” in our database than we are in a
position to interpret—it contains patterns that are beyond our analytic scope and/or are
highly localized. Since all these issues correlate with poorer fit between our hypothesized
factor loadings and the actual clustering of amenities, and since we constructed these
theoretical categories to represent something different from the mere copresence of
amenities, we constructed our own pragmatic method for testing how well our measures of
scenic meaning perform.
Rather than rely on traditional measures of statistical fit, we tested the construct validity
of our scenes dimensions by postulating an extensive set of falsifiable hypotheses
involving (what we believe to be) measures of particular scenes and then determining
whether these hypotheses are supported empirically, as reported in chapters 4, 5, and 6.
Our logic of validity assessment is that if we have poorly measured scenes or our theory of
scenes does not provide a consistent and meaningful way of understanding relevant
cultural meanings, then we should not observe the relationships posed by our hypotheses.
Part of providing an extensive set of hypotheses in Scenescapes has been to demonstrate a
broad pattern of results confirming the presence of expected relationships, which we take
to mean that we have created a sufficiently specialized and sensitive way of measuring
what we call scenes using the indirect evidence of amenities.24
To carry this out, we used our matrix of coder scores to calculate what we call
performance scores, which represent a way to aggregate information about the expressive
content embodied in our data sets. In essence, performance scores summarize the degree
to which the typical amenity in a place affirms or attacks each of the 15 dimensions of
theatricality, authenticity, and legitimacy outlined in our theory of scenes. They provide an
overall profile of the scene indicated by the set of amenities in a place, allowing for the
fact that the same dimension (e.g., transgression) can be affirmed by many different
amenities (e.g., body piercing studios and tattoo parlors).
The performance scores combine the scores assigned by coders to each amenity with
data on the number of each type of amenity located in a zip code. The discussion of
“transgressies” in chapter 3 outlines how performance scores are computed in clear and
intuitive terms. Computing performance scores is actually quite simple conceptually. Take
a hypothetical zip code, Zip Code #1. One calculates Zip Code #1’s transgression
performance score as follows: Suppose Zip Code #1 has five total amenities: four body
piercing studios and one Catholic church. Suppose also that body piercing studios were
scored 5 on transgressive theatricality while Catholic churches were scored 1. Multiply the
number of each type of amenity (4 body piercing studios, 1 Catholic church) by that type’s
transgression score (5 and 1). Sum the product and you get 21. Zip Code #1’s total output
of transgressive theatricality, which we sometimes refer to as its intensity score, is 21.25
Now divide that total output by the total number of amenities in the zip code (in this case,
5). The result of that division, 4.2, is Zip Code #1’s transgression performance score.
A different zip code, say, Zip Code #2, with four Catholic Churches and one body
piercing studio, would thus have a transgression performance score of 1.8. A greater share
of the amenities in Zip Code #1 indicates the presence of transgressive theatricality. Here
is another similarity to factor analysis—but instead of showing that the amenities in a zip
code tend to point toward a statistical regularity, performance scores show which zip
codes’ amenities point toward theoretically significant dimensions of cultural meaning. To
include an additional amenity in the calculation of a performance score, one need only add
it into our matrix and include its dimensional score. Figure 8.2 illustrates the computation
process.
Figure 8.2
This figure illustrates how to compute performance scores.
The 15 performance scores taken together thus represent a standardized measure of a
location’s scene, a holistic reconstruction of the scene detected in that location. Other
measures are no doubt possible and necessary, as is on-the-ground ethnographic work that
can capture subtle variations of amenity usage and meanings—we have explored
alternative constructions of our scenes measures and encourage others to do so as well.26
That said, this approach represents a way of constructing scenes measures that can be
easily repeated. For example, performance scores have been successfully created using
data sets similar to BIZZIP and YP from Canada, France, Spain, Japan, Korea, and Poland,
and we are refining methods of performing cross-national scene comparisons.
We tested the sensitivity of the performance scores to the number of amenities included
in their calculation by recomputing several scores with smaller numbers of amenities.
Changes were generally small, which indicated to us that individual amenities are unlikely
to be biasing our measures. Such small changes also increased our confidence in the
construct validity of performance scores. The online appendix section on sensitivity
checks details some of these analyses.
We have pursued many such alternative constructions, methods, and sensitivity tests.
Combining amenities, moreover, yields much more cultural specificity than any single
amenity can, so that national averages become modified by local context. Thus, as we saw
in chapter 3, the correlations among amenities and dimensions often vary across regions
and cities in ways that reveal their specific characters: for example, charisma is correlated
with neighborliness in Chicago but with self-expression in Los Angeles. Looking for how
relations (e.g., between charisma, self-expression, and neighborliness) shift across
contexts in this way permits us to join our cross-national focus with local specificity.
Measures That Combine Performance Scores
The performance scores are our main measures of the 15 dimensions of scenes. We
analyzed them in many ways. The simplest is to treat them separately, for instance, in
analyzing the separate impacts of self-expression, glamour, and tradition on economic
development, as in chapter 4. However, the theory of scenes suggests we look to
combinations of dimensions as well. So too does descriptive analysis of the performance
scores. For instance, if we look only at the national average performance scores for all US
zip codes, we find that that the average zip code positively affirms both the legitimacy of
tradition and of self-expression—that is, the national average performance scores for selfexpression and tradition are both positive. This is somewhat misleading, however, as the
two performance scores are negatively correlated. That is, many places are high in
tradition; many are high in self-expression; but places high in one are usually low in the
other. To account for the fact that scenes are combinations of positive and negative
relations to many dimensions of meaning, we placed a high priority on capturing
combinations of the performance scores. We did so in a number of ways.
One way to combine performance scores is simply by creating a multiplicative
interaction term for two or more dimensions, as in our analysis of self-expression times
transgression in chapter 5 and below. Another approach we explored (but ultimately did
not include) is to calculate the average sum of several dimensions for a geographic area.
And still another approach is to compare a zip code’s actual performance scores across the
15 dimensions to the scores that a theoretically important ideal-typical scene would
receive, as in our “bliss point” measure of Bohemia in chapter 4 (examples of the formulas
for computing these types of combinations are in the online appendix).27
Exploratory factor analysis offers another helpful way to draw out how scenes combine
in situ. We created factor scores using all 15 dimensions of the YP and BIZZIP data. The
six factors on which we have focused most attention in our analyses are summarized in
table 8.4. We discussed these factors because they had clear resonance with key scenes
from classical social, urban, and cultural theory.
Table 8.4. Factor score weights for performance scores
LA-LA
Urbanity Land
(YP1)
(YP2)
Rossini’s
City on a
Tour (YP3) Hill (YP4)
Renoir’s
Nerdistan Loge
(BZ3)
(CBP3)
Traditionalism
−0.786
0.384
0.031
0.438
−0.176
0.100
Selfexpression
0.307
−0.326
0.860
0.005
−0.210
0.398
Utilitarianism
0.836
0.003
−0.056
0.190
0.355
−0.363
Charismatic
−0.788
−0.030
−0.132
0.492
−0.127
0.734
Egalitarian
−0.087
0.185
−0.005
0.948
−0.038
0.176
Neighborliness −0.899
0.230
−0.237
0.353
−0.021
0.107
Formality
−0.840
−0.040
−0.390
0.040
0.603
0.571
Exhibitionism
−0.015
−0.885
0.006
−0.049
−0.007
−0.166
Glamour
0.417
−0.756
0.194
−0.450
0.063
0.870
Transgressive
0.853
−0.353
0.275
−0.320
−0.181
−0.114
Rational
0.834
−0.064
0.394
0.060
0.651
−0.217
Localism
0.051
0.235
0.885
0.047
−0.051
−0.015
Statism
0.873
−0.154
0.498
−0.135
0.102
0.033
Corporatism
0.856
−0.214
0.048
−0.170
0.287
−0.320
Ethnicity
0.183
−0.173
0.295
−0.192
−0.716
−0.010
Note: This table shows results of factor analyses applied separately to our YP and BIZZIP performance scores. It shows
the first four factors from our US YP performance scores. Because we also analyzed them in chapter 5, we show
Nerdistan, the third factor from the US BIZZIP performance scores, and Renoir’s Lodge (CBP3), the third factor from
the Canadian CBP performance scores. The first two BIZZIP factors extracted joined dimensions similar to YP. Results
for LA-LA Land reported in the text reverse its sign for easier interpretability, that is, in the chapter 5 bubble figures, a
positive coefficient for this factor indicates a positive relationship to glamour and exhibition. Key dimensions are in
bold. Extraction method: principal component analysis. Rotation method: Oblimin with Kaiser normalization.
The first US factor accounts for approximately 44 percent of the total variance among
the 15 dimensions, and we described it in chapter 3 under the label Communitarianism
versus Urbanity. On one end of the spectrum are Urbane scenes of transgression,
utilitarianism, reason, state, and corporation, which have the strongest loadings, followed
by glamour and then self-expression. On the other end are Communitarian scenes of
tradition, neighborliness, charisma, and formality. In essence, the first factor summarizes
in a single number the most powerful cleavage dividing the American scenescape. We
therefore include it in our core set of control independent variables. This is
methodologically significant: though we describe and analyze
Communitarianism/Urbanity at times, we are often less interested in the development
consequences of a generic Gemeinshaft/Gesellschaft scene and more interested in the
specific impacts of, say, a self-expressive scene net of, or over and above, this generic
difference. Including both the Communitarian/Urbanity factor and some individual
variables (like the self-expression performance score) permits us to identify their separate
effects, though not perfectly since some factors include multiple individual variables, as
we discuss. The other three YP factors (LA-LA Land, Rossini’s Tour, and City on a Hill)
were featured in chapter 5, along with the third BIZZIP factor, Nerdistan. We include the
third Canadian factor (from Canadian Business Patterns, similar to BIZZIP), Renoir’s
Loge, in table 8.4 because it was analyzed in chapter 4.
We experimented with other ways to measure the sorts of complex scenes outlined in
chapter 2. One technique was coding our data directly to measure, for instance, the
concepts of Bohemia or Disney Heaven. Another was to create ad hoc indexes based on
smaller subsets of amenities, usually by summing them, as in our New Con or Blue Blood
indexes.28 Others can adapt these and additional approaches to create indexes of their
favorite concepts for urban comparisons. Dozens of students have used these data for all
sorts of purposes.
Methods of Analysis: General Analytical Approach, Standard Method of
Analysis, and Modeling Context
One part of detecting scenes involves the careful construction of the best possible
measures of their presence. But an equally important part of demonstrating the validity of
scenes measures is confirming that these measures exhibit relationships with other
variables that are both expected and consistent with theory.
The question then becomes, what conditions have to be met before we consider our
results robust? Part of the answer involves accounting for known relationships and likely
confounders among common (and not so common) variables and our outcomes—that is,
accounting for potential spuriousness. The other significantly more complex part of the
answer involves choosing the appropriate multivariate methods of analysis. We discuss
both in turn.
General Analytical Strategy: The Core and More
Most multivariate analysis in Scenescapes includes a set of variables that measure key
factors associated with urban development. Largely drawn from the US Census of
Population, they typically represent aspects of the urban environment commonly studied
by urban economists, geographers, sociologists, and public policy advisors when
analyzing the outcomes we employ. Our general strategy is to include this set of
independent variables drawn from past research (which we term “the Core”) to account for
the influence of more traditional factors. The Core includes eight independent variables:
population size, percent of population who are nonwhite, median gross rent, percent
college graduates, percent Democratic vote for president, crime rate, the location quotient
of cultural jobs, and the Urbanity factor score. Including the Core in multivariate analysis
tests for possible spuriousness of our scenes measures. We also often explored how scenes
variables mediate relationships of other variables with our outcomes.29
In order to connect our hypotheses to ongoing academic debates, our main analytical
chapters used basic outcome measures similar to those employed by leading researchers in
the subfield studying each dependent variable. In many analytical chapters, we employed
other variables relevant to the specific issues discussed there; usually these were included
in addition to the Core group of independent variables. These other variables include, for
instance, technology jobs, neighborhood walkability, evangelical Christians, age, zip code
rent, and the like. Often they are an integral part of the hypothesis being tested. Sometimes
they supplement the Core, representing additional controls when theory or past research
suggests their relevance. All variables are listed in the online appendix, together with basic
descriptive statistics.
Performance Scores as Independent Variables
Performance scores are often key independent variables of interest in our models.30 That
is, Scenescapes typically asks what follows from the presence of a type of scene rather
than what encourages that type of scene. This by no means implies that we believe scenes
are uncaused causes—we illustrate some sources of scenes below. Nor does highlighting
performance scores and amenities imply that these are the only or primary drivers of
development. We often stress how our amenities-based measures shift relationships of
other important variables. We seek to add scenes to the analytical mix, not to replace other
important variables.
Nevertheless, as our primary interest is in scenes, we have constructed our hypotheses
to explicitly test whether our measures demonstrate theoretically consistent relationships
with these outcomes. As suggested above, these hypotheses themselves help assess the
robustness of patterns in which scenes may operate as independent variables. Yet the
possibility that performance scores are actually measuring some other more traditional
feature of the urban landscape is always a concern to address systematically.
To assess the degree to which scenes measures might be proxies for other factors, we
examined their correlations with many sociodemographic and other variables—the Core
and many of the “other variables” listed in the online appendix (26 in all). The lack of
strong relationships is very striking. The average absolute value of Pearson correlations
between the YP and BIZZIP performance score measures of scenes and the 26 variables is
below 0.1 (0.087 for YP, 0.074 for BIZZIP). As we might expect, education and rent show
significant average correlations with many performance scores, though the connections are
weak to moderate: their average correlation with the YP and BIZZIP performance scores
is about 0.16 (and change in college graduates, often given much weight in analyses of
urban change, is even lower: 0.03).
To further scrutinize the analytical independence of the performance scores, we
analyzed each of the 15 performance scores as dependent variables, including the
aforementioned 26 as independent variables. The extent to which variance in performance
scores is explained by this expanded model is low: the adjusted R-squared for nearly all
performance scores is below 0.2 (only a few are slightly above), with most being
considerably lower. The same holds even for the combinatorial measures of scenes: the
Core predicts our main factor score relatively weakly, with the adjusted R-squared at only
0.13. All of which is to say that scenes cannot be explained away as relabeling old
concepts and measures with new names. What the scene is cannot be read off reports of
education levels or average incomes, since many places with similar levels of each have
very different scenes.
Similarly, our main analyses presume that scenes are relatively stable. But scenes
clearly are often in flux, changing in nonrandom ways that may influence our analyses. A
scene may owe its self-expressive qualities in 2000 to the fact that college graduates
moved there in 1980 and slowly started building (or inspiring the building of) amenities to
suit their tastes, changing the scene accordingly. Still, even though scenes change to
reflect the tastes and values of residents (not to mention visitors, business owners, and
politicians), after they emerge, they can “take on a life of their own” and acquire
“emergent properties” that go beyond whatever processes generated them. For instance,
once a scene that offers opportunities to cultivate individual self-expression emerges,
however it got there, it can provide continuing attractions that often outlast the specific
people or processes that stimulated its creation.31
Given the limits of our data, we have explored this hypothesis in a number of ways.
One analysis of stability of our scenes measures over time used four time points (1998,
2000, 2001, and 2004) and county-level data. The goal was to understand the “stickiness”
of scenes by looking at how quickly scenes change given a certain degree of churn in the
numbers and types of amenities within a county. On average, the total number of coded
amenities in a county increased by 7 percent from 1998 to 2004. Conversely, performance
scores associated with all 15 dimensions shifted, on average, less than 1 percent during the
same time period. Analysis of Canadian performance scores also revealed that scenes are
not temporally fleeting: the average correlation of the 2001 and 2011 Canadian FSA
performance scores was 0.77; 2007 and 2011 were correlated 0.86 (these are the years for
which we have data). Here is some evidence of the “rolling inertia” that Molotch,
Freudenburg, and Paulsen (2000) suggest make up the character of places. More broadly,
we locate the difficulties we face in making causal claims about scenes with a set of
general concerns shared in the social sciences at large, considered below in our discussion
of “the chicken and the egg.”
Multivariate Methods
Choosing a multivariate method for testing relationships between various measures of
scenes and our outcomes is a crucial decision that means balancing parsimony and
accuracy. Simpler methods are preferable for ease of interpretation, but scenes pose a
unique challenge by their explicitly spatial nature. Residents and nonresidents frequent a
scene, and the expanse of a scene may be a few buildings, a few city blocks, or even a few
miles. How do we make sense of these scales analytically, acknowledging variation while
still applying a method that consistently picks out the appropriate “signal” for exploring
the relationships we hypothesize?
A major issue in choosing a multivariate method for scenes analysis involves units of
analysis and their geographic scope. Substantial questions arise as to the appropriate
geographic scope of many variables in our models, but especially regarding a scene’s
impacts. Scenes might cross zip codes, and their attractions might extend to people who
live nearby but not in the same zip code. Similarly, a variable like crime rate is reported at
the county level but depending on population density (and other factors) the effects of
crime might be significantly more localized, or spread around the county as a whole. We
address these concerns in the section below on modeling context. In general, however, we
started with the smallest reasonable units and then compared results for successively larger
units as one method to assess the size of distinct catchment areas, since catchment areas
vary for different scenes and processes.
Another important issue is connected with the nature of large data sets. Since scenes
analysis tends to involve thousands of cases, we often observe highly statistically
significant yet quite modest numerical relationships, like a Pearson correlation of 0.15.
This is both the blessing and curse of having so many cases, requiring us to be
circumspect in the claims we make about the strength of observed relationships. One
simple solution we have employed is to not only report standardized regression
coefficients, or significance levels, but also often graph the relative size of these
coefficients so that readers can easily compare the importance of scenes with the
importance of other variables.
Along with large numbers of cases, our scenes database involves some items that were
either not available in a consistent manner nationally or simply exhibit distributionally
troublesome traits for statistical modeling, such as an excess of zeros. Typically, we
observe excess zeros in relatively rare amenities, like film studios, and largely solve this
issue by creating additive indexes of several amenities when exploring clusters of
amenities outside of performance scores. Similarly, variables are transformed when
reasonable to do so, though persistent issues of missing data were more difficult to
address. For the most part we assume that data are missing completely at random
(MCAR), but we do not employ imputation methods since we lack the expertise/resources
to implement a proper imputation scheme or decide whether to impute amenities or
performance scores (for instance).32
Finally, the indirect nature of our evidence had to be considered when choosing a
multivariate method for scenes analysis. Just as our performance scores represent
imperfect indicators of a scene, so too will any large-scale quantitative analysis
imperfectly capture the dynamics of the hypotheses. The complex narrative that leads
some young professionals to live in high crime areas due to the presence of an appealing
scene cannot be adequately told by standard methods.
This is where work like that of Richard Lloyd in Neo-Bohemia and other more
ethnographic approaches becomes extremely valuable for validating or challenging our
results. Where possible we include tidbits of ethnographic observation intended to flesh
out the cold numbers produced by multivariate analysis. The boxes in the text are often
critical in adding more subtle meaning to our interpretations.
Standard Method of Analysis
Determining the simplest multivariate method possible for analyzing the relationship
between scenes and our outcomes turns on addressing the issues identified above. The
goal is to detect evidence for a relationship that assesses our original hypothesis and can
be clearly translated into a narrative for further investigation.
Linear regression is the simplest multivariate method we could have employed, and
largely for this reason we began with ordinary least squares (OLS) regression as our
standard multivariate method of analysis. We follow a long tradition here. Our analyses
generally began with OLS models for each outcome, included the Core as independent
variables, and explored both listwise and pairwise deletion. This method of beginning with
a set of core variables and adding other measures to the analysis as needed has been robust
in past works (cf. Clark 2004, 2011a). To these models we add other variables, often based
on past research, one or a few at a time, depending on the substantive proposition. This
allows us to assess both their direct effects on the outcome and their possible indirect
effects on the relationships involving Core variables.
Some variables were too strongly intercorrelated to permit including them all
simultaneously. We normally omitted independent variables when two or more exhibited
Pearson correlations that exceeded 0.5, but we also relied on variance inflation factors
(VIFs) to detect problematic multicollinearity. For most models, the VIF of independent
variables does not exceed 4, and in no case does it exceed 10.
The assumption of independence of cases in classic linear regression (ordinary least
squares) is clearly broken when we combine data whose units of analysis differ in
geographic scope (e.g., assigning the same county total population to each of its zip
codes). Moreover, linear regression fails to account for spatial configurations, by assuming
independence even between two zip codes in the same city neighborhood, as if they were
tiny prisons whose residents never left and which outsiders never visited. This is one of
several standard assumptions of OLS that are often hard to justify in practice.
To check whether violating linear regression assumptions was substantively biasing our
results, we tested many variations in model specification and replicated our main analyses
using other more complex methods (like mixed/multilevel models) in comparison to OLS.
Out of 527 total coefficients we examined, we found that 12 percent disagreed between
OLS and mixed models (i.e., switched from positive or negative to insignificant, from
insignificant to positive or negative, or from one sign to the other). Differences were
slightly smaller for scene variables (10 percent). While not as large as one might imagine,
this was enough to convince us to make mixed models the default method of analysis in
Scenescapes, rather than OLS, because they more directly take account of the
embededness of zip code scenes in broader (e.g., county) contexts.33 Still, multilevel
models are just one approach to explicitly modeling context, and combining this approach
with others can enrich our understanding of some of the processes investigated in
Scenescapes. To illustrate this general statement, we take a deep dive into one analysis—
the chapter 5 examination of the relationship between self-expression, transgression, and
change in the 25- to 34-year-old share of the population.
Modeling Context
We explored several additional methodological strategies to check and extend the standard
methods typically reported in Scenescapes. One key area for such exploration concerns
spatial context—the idea that the meaning and impacts of scenes may vary depending on
where they are located, just as much as other variables may operate differently depending
on their proximity to a given scene. “Proximity alters performance” was the slogan for this
idea in chapter 3. We illustrated this concept with relatively simple methods, such as
showing in chapter 3 how correlations between charisma, self-expression, and
neighborliness vary in Chicago versus Los Angeles, or showing in chapter 4 how the
impact of Bohemian zip codes on economic growth depends on how communitarian or
urbane their surrounding counties are.
Here we link a particularly intriguing finding from chapter 5—that 25- to 34-year-olds
were increasing between 1990 and 2000 in transgressive but not self-expressive scenes—
to more sophisticated methods that progressively add more depth and detail to our
understanding of the role of spatial context in scenes analysis. Scenes, we have stressed,
are not just one more variable to add to a multivariate model; they are also contexts that
potentially transform the very meaning of other variables. Systematically analyzing such
contexts, however, is challenging methodologically. Indeed, only recent innovations make
it possible to consider a range of indirect, interactive, and multilevel processes in ways
that allow us to test (and relax) some of our assumptions regarding space and scenes.
Consider these more sophisticated techniques for the chapter 5 analysis of
transgression, self-expression, and 25- to 34-year-olds. We present three ways of further
analyzing this relationship: multiplicative interaction terms, parameterization of spatial
adjacency among scenes, and calculation of performance scores using different catchment
areas—often exploring the extent to which the nested structure of our data biases results
from traditional OLS models. Each approach has its distinctive strengths and weaknesses,
but together they help illustrate some contextual dynamics of scenes and link scenes
analysis with cutting-edge work on modeling local area and spatial effects. Perhaps more
importantly, attacking the same problem from multiple methodological angles permits a
more creative and subtle interpretation of how the scenic context of a location can
transform its meaning.
Interaction terms—within zip code. One classic approach to modeling context in a
linear regression framework is to create multiplicative interaction terms. This is a common
way of gaining a potentially useful picture of how two variables mediate each other. Given
the standard nature of this method of parameterizing context for use in modeling, we often
explored the significance of such multiplicative interaction terms. Table 8.5 summarizes
results of this and subsequent analyses.
Table 8.5. Ordinary least squares regression models with change in 25- to 34-yearolds as outcome
Interaction
Variables
Base
Within zip code
Neighbor
Percentage age 25–34 (1990)
−0.643***
−0.644***
−0.642***
(−37.77)
(−37.82)
(−37.11)
−0.022***
−0.023***
−0.024***
(−5.54)
(−5.67)
(−5.90)
0.017***
0.017***
0.017***
(10.73)
(10.89)
(10.91)
0.358***
0.356***
0.352***
(12.73)
(12.67)
(12.54)
−0.156**
−0.086
−0.074
(−2.25)
(−1.19)
(−1.03)
0.762***
0.766***
0.755***
(15.28)
(15.37)
(15.26)
−0.138***
−0.143***
−0.182***
(−3.71)
(−3.85)
(−4.89)
0.194***
0.190***
0.173***
(6.15)
(6.04)
(5.53)
0.103***
0.103***
0.108***
(4.31)
(4.34)
(4.58)
−0.143***
−0.146***
−0.166***
(−5.59)
(−5.71)
(−6.35)
−0.125***
−0.097**
−0.046
(−3.38)
(−2.55)
(−1.12)
0.407***
0.394***
0.370***
(5.75)
(5.55)
(5.19)
0.082***
0.044*
Percentage college degree (1990)
Percentage nonwhite (1990)
Cultural industry clusters (1998)
Urbanity
Population (county, 1990)
Median gross rent (county, 1990)
Percentage Clinton vote (county, 1992)
Employment ratio (county, 1994–2001)
Natural amenities scale (county)
Self-expression
Transgression
Self-expression × Transgression
(3.51)
Transgression (neigh.)
(1.86)
0.289***
(4.73)
Self-Expression × Transgression (Neigh.)
0.302***
(5.39)
Constant
−3.418***
−3.435***
−3.364***
(−92.10)
(−92.64)
(−83.94)
Observations
24,667
24,667
24,459
R-squared
0.404
0.404
0.404
Degrees of freedom
13
14
16
Log-likelihood
−65,969
−65,961
−65,172
Note: This table indicates that, from 1990 to 2000, the percentage of 25- to 34-year-olds in a zip code increased in
places where adjacent zip codes were more transgressive, and that this effect was enhanced when such places possessed
a more self-expressive scene. Robust t-statistics in parentheses.
***p < 0.01
**p < 0.05
*p < 0.1
Consider the base model in table 8.5 reporting OLS regression coefficient estimates for
our chapter 5 example of change in 25- to 34-year-olds across all US zip codes from 1990
to 2000. This model separates self-expression from transgression: self-expressive scenes
show less than average growth in the 25- to 34-year-old population, while transgressive
scenes show more than average growth. We may then raise the question of context: Does
the level of transgression in a self-expressive scene alter these relationships or exhibit its
own unique effect?
In our example, the column of table 8.5 labeled “Interaction—within zip code” presents
results for an OLS regression where a multiplicative interaction term for self-expression
and transgression has been added to the base model. We call this a within–zip code
interaction to highlight how a heightened level of transgressiveness within a given zip
code may alter the impacts of that self-expressiveness within that same zip code. We
contrast this with a neighbor interaction approach that highlights how a heightened level
of transgressiveness among adjacent zip codes alters the effects of a given zip code’s selfexpressiveness, elaborated in more detail below.
As table 8.5 shows, in the case of the within–zip code interaction, the main effects of
self-expression and transgression on change in 25- to 34-year-olds remain the same:
negative for the former, positive for the latter. At the same time, the estimated regression
coefficient for their interaction is positive, indicating that the presence of one amplifies the
effect of the other.
Interpreting interaction terms can be arduous and requires a sound understanding of
how the magnitude of estimated coefficients for both main effects and the interaction term
operate. Reasoning in terms of how scenes shape a context can sometimes add substance
and specificity to the interpretation. One method is to graphically display the specific
interaction result, as we did in several cases in chapters 4, 6, and 7.34 More specifically,
one can graph predicted values of the outcome based on the average value of other
variables and a demonstrative manipulation of the two variables that constitute the
interaction. One way to do so is by plotting predicted responses in the outcome given
continuous variation in one variable while holding the other variable at a constant value.
Plotting three lines shows the predicted response of our outcome given a continuous
change in one component of the interaction term and three categorically different levels of
the other component, holding other variables constant. Thus in chapter 4 we used this
technique to show how low, average, and high levels of the Renoir’s Loge scene (a factor
score combination of charisma, glamour, and self-expression) shift the relationship
between artist concentrations and economic growth.
For table 8.5, we simply note that the regression coefficient for self-expression is on par
with that of the interaction term. This implies a relatively complicated state of affairs.
Self-expressive scenes are negatively related to change in 24- to 35-year-olds, and they
exhibit a net neutral relationship in the presence of a transgressive scene but an especially
negative relationship in the presence of antitransgressive scenes.
Interaction terms—neighboring zip codes. While within–zip code interactions
involve relatively standard methods, an open methodological question regarding scenes,
mentioned already, is their typical geographic extent. A more novel method to tackle this
problem is to extend traditional multiplicative interaction terms to incorporate a form of
spatial dependence. The idea is to create variables that capture characteristics of
neighboring zip codes, and parameterize them for use in subsequent modeling.
Other ways of modeling spatial dependence are possible, and we present one alternative
below, but adjacent zip codes (those that touch geographic borders) are a reasonable place
to start. After the zip code of residence, residents likely have easiest access to the scenes
in the immediate vicinity of where they live—these adjacent areas are the most likely to be
within walking distance and require the lowest travel time. (This is one implicit
assumption of studying how scenes relate to demographic and economic trends using zip
codes.) Thus we constructed measures for each scene dimension for both YP and BIZZIP
based on the average performance score of immediately surrounding zip codes.35
Avoiding spatial autocorrelation is often the main rationale for investigating how a
given analysis may be biased by failing to take into account space. A classic case is racial
segregation. If underinvestment in inner-city neighborhoods occurs because such
neighborhoods all tend to be physically clustered (e.g., in ghettos) and thus share a larger
area of economic deprivation, then analyzing the characteristics of each neighborhood
separately will not capture this larger context. Since it is now well established that
neighborhoods where many African Americans live are highly likely to be near other such
neighborhoods, ignoring this context can lead policy makers to develop inefficient or
ineffective programs for urban revitalization, to the extent that the success of local
interventions depends in some part on factors operating at a scale larger than the zip code.
This well-known example provides a convenient way to assess how well our adjacency
technique captures spatial autocorrelation, since the mean value of adjacent zip codes is
not a common way to address potential spatial dependence of a variable.36 We thus
performed the same procedure on percent nonwhite in a zip code as we did for our
performance scores: we computed the average percent nonwhite for all adjacent zip codes
for every US zip code. We then calculated a simple Pearson correlation between percent
nonwhite in a zip code and average percent nonwhite in adjacent zip codes. Results
indicated a very strong direct relationship between the two (above 0.8), suggesting that if
scenes are strongly spatially autocorrelated, then our technique would pick this up as well.
Are zip codes with similar scenes likely to be near one another? By comparing the
performance score of a given zip code (i.e., the target zip code) with the mean
performance score of adjacent zip codes (i.e., neighbors), we find quite different results
than for nonwhites: there is little spillover of scenes across zip codes, or general spatial
ordering of scenes. Tables 8.6 and 8.7 report Pearson correlations between each
dimension’s performance score in a zip code and the neighboring zip codes’ mean
performance scores along each dimension, for YP and BIZZIP respectively.
Table 8.6. Pearson correlations between yellow pages (YP) performance scores of
target zip code and neighboring zip codes
Note: This table indicates that the scene in one zip code is a poor predictor of scenes in adjacent zip codes.
**p < 0.01 (2-tailed)
*p < 0.05 (1-tailed)
Table 8.7. Pearson correlations between Zip Code Business Patterns (BIZZIP)
performance scores of target zip code and neighboring zip codes
Note: This table indicates that the scene in one zip code is a poor predictor of scenes in adjacent zip codes.
**p < 0.01 (2-tailed)
*p < 0.05 (1-tailed)
Tables 8.6 and 8.7 go beyond looking for simple spatial autocorrelation, however.
Scenes may not be spatially autocorrelated along single dimensions but rather show spatial
patterns across different or multiple dimensions. For example, self-expressive scenes may
usually be next to transgressive scenes but rarely next to other self-expressive scenes.37
Even casting such a wide net, we find no strong correlations suggesting a clustering of
scenes across zip codes. In fact, Pearson correlations never reach 0.4 in magnitude and
rarely exceed 0.3. This suggests that the “right” scale for studying scenes—at least using
the kinds of data and analyses in Scenescapes—is generally unlikely to be much larger
than the zip code. This result offers some justification for using zip codes as the main unit
for analyzing scenes, and suggests spatial autocorrelation is generally less a source of bias
in the case of scenes than in the case of race (as measured for the United States in this time
period).
Analyzing adjacency is valuable not only for avoiding statistical bias. One can also
interpret how much spatial proximity shifts the impacts of other variables.38 Thus, armed
with the knowledge that neighboring zip codes generally do not replicate the scene of the
target zip code, we can gain further insight into how the effect of that scene is mediated by
its surrounding scenic context. That is, because zip codes are generally weakly correlated
with the scenes of their neighboring zip codes, we can test hypotheses about how the
scenes in the neighboring zip codes may alter the character and consequences of scenes in
the original target zip code.
Returning to our example, this approach allows us to explicitly model how the spatial
proximity of self-expression and transgression shifts their impact on 25- to 34-year-old
population growth. We do this by adding measures of average transgressiveness in
neighboring zip codes to the model. The last column of table 8.5, labeled “Interaction—
Neighbor” adds (a) the average transgression performance score of neighboring zip codes
and (b) the multiplicative interaction of this measure with the original zip code’s selfexpression performance score. The estimated regression coefficients for these variables
tell us (a) whether neighboring zip codes’ transgressiveness has an independent effect on a
zip code’s change in 25- to 34-year-olds and (b) whether self-expressive scenes next to
transgressive scenes shift outcomes.
Results suggest that this spatial configuration modeling not only matters but accounts
for the independent effect of self-expressive scenes. Self-expression alone, recall,
suppresses change in 25- to 34-year-olds. However, when we add the transgressiveness of
adjacent zip codes, self-expression becomes insignificant. Further, the positive
relationship between transgression and change in 25- to 34-year-olds extends beyond the
target zip code—whether a zip code’s neighboring zip codes have transgressive scenes is
actually more strongly related to our outcome than the transgressiveness of the target zip
code itself.
Finally, in considering the joint effect of transgressiveness and adjacent selfexpressiveness, we observe a surprisingly powerful relationship that would have gone
unnoticed otherwise. Specifically, zip codes high in self-expression also adjacent to zip
codes high in transgression were more likely to increase in 25- to 34-year-olds than zip
codes that were only more transgressive. This cross–zip code interaction is also more
strongly related to growth in 25- to 34-year-olds than the within–zip code interaction
between self-expression and transgression. The spatial configuration of scenes, in other
words, may have a pronounced effect on certain outcomes—in this case being near a
transgressive scene heightens the allure of self-expression over and above simply being in
a transgressive scene. For many young people, that is to say, transgression may be more
appealing when they do not have to spend all night surrounded by red lights and loud bars
but can retire to a less edgy, but still interesting, self-expressive scene.39
Multilevel models. Employing this relatively simple spatial measure thus provides a
refined level of analytical control over the social environments we are studying. Yet thus
far we have still been violating a principal assumption of linear regression—independence
of cases—by including county-level variables in multivariate models without accounting
for the clustering of zip codes within counties. We next explore how analyses may be
further refined through a method designed to model such clustering.
Social scientific data is often collected at multiple, nested levels. The now classic
example, explored by Raudenbush and Bryk (2002), is the nesting of students within
classrooms, where student performance is not just a function of individual characteristics
but also of classroom characteristics. Their hierarchical linear modeling (HLM) is largely
associated with such one-to-one hierarchical relationships between levels of analysis,
though the analytical approach is known by many names: mixed models, multilevel
models, random-effects models, and so on. Whatever the label, the central premise is that
we must account for the multilevel structure of the data because not doing so may produce
biased results. For example, in the case of student performance, comparing two
demographically identical students fails to account for teacher effectiveness and peer
influences unless these differences in the two different classrooms are explicitly modeled.
In the case of scenes, comparing two demographically identical zip codes from two
different counties fails to account for county-level characteristics—economic,
demographic, or political, like the presence of a Superfund site. An initial approach to this
issue was to utilize some county-level variables to capture context in zip code–based OLS
regressions. We did this by joining the two levels in a single data file, which simply
repeats the county values for each zip code within that county. This has the effect of
underestimating the standard errors for county-based variables, thus biasing the normal
significance computations.
Why investigate counties? The county is a larger and more sensible catchment area for
certain characteristics, like cost of living or wages or rent, where low transportation costs
allow individuals wider choices in location of residence. In other cases, such as crime rate,
we were limited to county-level measures because the data are not disclosed at a lower
level (by the FBI which adjusts noncomparable local crime data). OLS is a good first step,
but it does not fully account for the specific nesting of zip codes within counties.
We thus estimated the appropriate mixed models for our initial OLS regressions. While
multilevel models can allow estimates of regression coefficients that vary according to the
higher-level units of analysis (e.g., counties), we typically estimate random intercept
models (i.e., intercepts vary by counties), though we did explore some random-effects
models. This means that an average value for our outcome variable is estimated for each
county, but a single value is estimated for the regression coefficients associated with our
zip code–level variables. Our county-level variables (e.g., total population) are used to
model the county-specific average values of our outcome.
See below for the generic model specification for our outcomes using the Core as
independent variables:
(8.1a) Yij = β0j + β1j × CollProfLv90 + β2j × LevelNonWhite90
+ β3j × ARTGOSLG98a + β4j × YPFactorScore + rij
where
(8.1b) β0j = γ00 + γ01 × ITEM005 + γ02 × ITEM218
+ γ03 × ITEM108 + γ04 × CrimeRate1999county + u0j
HLM/mixed models in table 8.8 replicate the key OLS analyses in table 8.5.40 The OLS
regression results are effectively confirmed. Some standard errors shrink, but others
actually increase. This is unsurprising as the use of HLM allows us to more precisely
analyze the structure of our data, and we expect some differences in the magnitude and/or
significance of coefficient estimates in HLM versus OLS models. In every case, however,
estimates are consistent in terms of the direction and approximate magnitude of
relationships between our variables of interest and our outcome.
One further opportunity for spatial analysis that HLM affords is the ability to estimate
cross-level interaction terms. Rather than exploring the effect of having transgressive
neighboring zip codes, this approach explores how the impacts of self-expressive zip
codes depend on the transgressiveness of their surrounding counties. Doing so effectively
casts the spatial net wider, not only to the opportunities for transgressive experiences
adjacent to a given zip code, but to those experiences available (on average) throughout its
entire county. The “Interaction—Cross-level” model in table 8.8 reports results for such a
model.
Table 8.8. Hierarchical linear models with change in 25- to 34-year-olds as outcome
Interaction
Variables
Base
Within zip code Neighbor Cross-level
ZIP code level covariates
Percentage 25- to 34-year-olds (1990)
Percentage College graduates (1990)
Percentage Nonwhite (1990)
Cultural industry cluster
Urbanity
Self-expression
Transgression
−0.665*** −0.666***
−0.668***
−0.666***
(−26.29)
(−27.80)
(−27.02)
−0.029***
−0.029***
(−26.72)
−0.027*** −0.027***
(−4.63)
(−4.84)
(−5.17)
(−5.02)
0.015***
0.015***
0.015***
0.015***
(6.51)
(6.80)
(6.81)
(6.97)
0.340***
0.336***
0.327***
0.335***
(11.60)
(11.55)
(11.51)
(11.57)
−0.085
0.000
0.008
0.294***
(−1.24)
(0.00)
(0.11)
(7.01)
−0.078**
−0.065*
−0.069*
−0.032
(−2.15)
(−1.76)
(−1.87)
(−0.82)
0.328***
0.315***
0.297***
(4.93)
(4.66)
(4.62)
0.084***
0.055***
(3.78)
(2.59)
Self-expression × Transgression
Transgression (Neigh.)
0.343***
(5.07)
Self-Expression × Transgression (Neigh.)
0.243***
(4.30)
County-level covariates
Population (1990)
Median gross rent (1990)
Percentage Democrat vote share (1992)
Crime rate (1999)
0.843***
0.851***
0.846***
0.874***
(9.51)
(9.83)
(9.68)
(9.94)
−0.084
−0.090
−0.131*
−0.078
(−1.08)
(−1.19)
(−1.70)
(−1.04)
0.230***
0.225***
0.212***
0.222***
(4.73)
(4.76)
(4.37)
(4.64)
0.105**
0.107**
0.110**
0.117***
Crime rate (1999)
Employment ratio (1994–2001)
Natural amenities index
0.105**
0.107**
0.110**
0.117***
(2.35)
(2.39)
(2.46)
(2.68)
0.085**
0.085**
0.088***
0.085**
(2.42)
(2.45)
(2.59)
(2.50)
−0.174*** −0.178***
−0.215***
−0.165***
(−3.80)
(−4.76)
(−3.76)
(−4.03)
Transgression (county mean)
−0.094
(−1.15)
Cross-level interaction
Self-expression x Transgression (county)
0.355***
(5.40)
Constant
−3.384*** −3.397***
−3.378***
−3.372***
(−51.39)
(−52.87)
(−52.41)
(−53.85)
Level 2 variance
1.297
1.313
1.350
1.309
Level 1 variance
10.837
10.818
10.771
10.824
ρ (ICC)
0.107
0.108
0.111
0.108
N (counties)
2,625
2,625
2,625
2,625
N (ZIP codes)
24,465
24,465
24,465
24,465
Degrees of freedom
16
17
19
17
Log-likelihood
−64,718
−64,705
−64,670
l−64,711
Note: This table accounts for the nesting of zip codes within counties, something which table 8.5 does not. It shows that
when self-expressive zip codes are located in surrounding areas that are transgressive, their impact on growth in 25- to
34-year-olds increases. Bootstrapped t-statistics in parentheses (3,000 replications).
***p < 0.01
**p < 0.05
*p < 0.1
The “Interaction—Cross-level” results indicate that zip codes with self-expressive
scenes exhibit no independent effects on change in 25- to 34-year-olds. Only when selfexpressive zip codes are located in a transgressive county do such scenes exhibit a positive
relationship with change in 25- to 34-year-olds. This result suggests that the effect of
scenes, in this case transgression, may not be as localized as suggested initially by our
adjacent zip codes approach. It suggests that county effects may operate in addition to the
adjacent zip codes—as in the case of people who regularly commute across many
neighborhoods in the same county for jobs, religious worship, shopping, and scenes.41
These combined results of direct measures, standard within–zip code interactions,
neighbor interactions, and multilevel modeling suggest a few intuitive scenarios: (1) 25- to
34-year-olds are drawn to zip codes which are more transgressive, with the presence of a
self-expressive scene effectively unimportant in such zip codes; (2) 25- to 34-year-olds did
not move to self-expressive scenes unless such scenes were also transgressive or adjacent
to a transgressive scene, with the latter being the more powerful dynamic; (3) 25- to 34year-olds are drawn to self-expressive scenes located next to transgressive scenes. One can
also imagine a combination of (1) and (3).
A look at some examples helps clarify and interpret these scenarios. Consider first some
zip codes in Chicago’s North Side, near the Loop. These contain neighborhoods like
Wicker Park, Bucktown, Logan Square, DePaul University, Lincoln Park, Old Town, the
Gold Coast, and River North. All score high on self-expression.
But so too do zip codes in many small towns in Illinois. One example is Maeystown.
About an hour outside of St. Louis, Maeystown is a historic German village that is home
to Oktoberfest events, arts and crafts fairs, garden shows, and quaint B&Bs.42 Maeystown
accordingly has a high self-expression score. Looking at self-expression alone effectively
treats all these zip codes—Maeystown, Wicker Park, the Gold Coast—as the same.
But of course they are not the same, and a young person can tell the difference. We can
too, once we look beyond self-expression in isolation. Take Maeystown again: it has a
high self-expression score, a high local authenticity score, but a very low transgression
score. This is a mix potentially attractive to a baby boomer, but less to the typical 25- to
34-year-old.
Now return to Chicago. The zip codes containing Wicker Park, Bucktown, and Lincoln
Park have high self-expression scores. But they also have high transgression scores—they
are examples of a strong within–zip code interaction between self-expression and
transgression. To move here is to live among art galleries and festivals as well as
nightclubs, tattoo parlors, and alternative music venues.
The within–zip code interaction highlights the experiential difference between places
like Bucktown and places like Maeystown. The adjacency-interaction and multilevel
models, however, bring out what is distinct about places like the Gold Coast and River
North. Like Maeystown and Bucktown, they have high self-expression scores—but in
comparison to Bucktown and the other North Side zip codes, the Gold Coast transgression
score is relatively low, right around the national mean. In this respect the Gold Coast is
closer to Maeystown.
But, of course, there is a big difference: location. The Gold Coast and River North are
near many other zip codes with high transgression scores: south to the Loop, west to
Fulton River Park, and north to the Near North Side. And the average transgression score
in Cook County (in which the Gold Coast is located) is considerably higher than the
average transgression score of Maeystown’s county (Monroe). To move to the Gold
Coast/River North, that is, is to move to a place with interesting, but perhaps not very
edgy, galleries, boutiques, and restaurants. But just down the street are Chicago’s more
risqué haunts, which a Gold Coast resident can partake of—followed by a quick cab ride
home to a safer, and quieter, apartment (with a doorman). This would be hard to do in
Maeystown.
The example illustrates the general results. If we analyze self-expression scores alone,
we would not be able to tell the difference between a place like Maeystown and those
many Chicago zip codes that also have high self-expression scores. But once we see that
Maeystown (and similar places) (a) do not also have a high transgression score and (b) are
not near anywhere else with a high transgression score, then the difference between
Maeystown-esque and (a) Wicker Park/Bucktown-style scenes and (b) the Gold
Coast/River North–style scenes comes out loud and clear.
These contextual differences are all clear enough intuitively, but modeling them
statistically is difficult. At the same time, more sophisticated statistics often mean losing
sight of the lived experiences they are supposed to illuminate. This scenes approach to
modeling context shows how to do both at once, and how similar techniques could be
extended to other propositions about scenes and spatial context.
Catchment areas. Accounting for the scenes in adjacent zip codes is only one way to
incorporate space into a scenes analysis. Another approach is to incorporate the concept of
adjacency and catchment areas into the very construction of scenes measures. While
adjacency only incorporates immediately surrounding zip codes, catchment areas expand
this area to include various rings of zip codes extending outward from the target zip code.
Importantly, we can construct performance scores for a target zip code based on the
amenities within a certain radius of zip codes that surround it. Figure 8.3 illustrates the
conceptual and spatial differences between neighboring scenes and amenity catchment
areas.
Figure 8.3
Operationalizing spatial relationships
Key implications of catchment areas arise from how we theorize their meaning:
Catchment areas are a way to model the effective limit of residents’ vision when it comes
to available options for consumption. That is, residents may not consider certain amenities
to be available because they are “too far” away. Conversely, the amenities that constitute
their local scene may extend well beyond their zip code of residence. To examine these
possibilities, we recalculated performance scores using various radii.43 Table 8.9 reports
the Pearson correlations between these self-expressive performance scores, suggesting
that, despite producing similar values, choice of catchment area may add value to our
analysis of scenes. For example, scores calculated using only amenities in the target zip
code have a Pearson correlation of 0.343 with scores calculated using amenities from the
target and immediately adjacent zip codes. Zip code and immediately surrounding scenes
are similar but not identical.
Table 8.9. Correlations between self-expression performance scores using various
radii
Catchment area
R=0
R=1
R=2
R=0
1.000
R=1
0.343**
1.000
R=2
0.415**
0.774**
1.000
R=3
0.391**
0.726**
0.911**
R=3
1.000
Note: This table suggests that, while there is some spillover of self-expression between zip codes, the scene of a
location looks quite different depending on how large an area one considers.
** Significant at the 0.01 level (2-tailed)
To explore how different catchment areas may reveal further subtleties about the
dynamics of self-expression, transgression, and young people, we reestimated our
“Interaction—Neighbor” mixed model using performance scores based on four different
radii (R = 0 to R = 3). In table 8.10, the R = 0 model is identical to the original
“Interaction—Neighbor” model reported in table 8.8.
Table 8.10. Hierarchical linear models with change in 25- to 34-year-olds as
outcome, varying catchment areas
Catchment Area
Variables
R=0
R=1
R=2
R=3
−0.668***
−0.674***
−0.671***
−0.669***
(−27.51)
(−27.97)
(−28.09)
(−27.29)
−0.029***
−0.033***
−0.031***
−0.030***
(−5.20)
(−6.16)
(−5.76)
(−5.47)
0.015***
0.015***
0.014***
0.013***
(7.21)
(7.15)
(6.39)
(5.72)
0.327***
0.282***
0.314***
0.330***
(11.67)
(10.19)
(10.86)
(11.51)
0.008
0.084**
0.144***
0.162***
(0.11)
(2.34)
(4.23)
(4.74)
−0.069*
−0.212***
−0.378***
−0.513***
(−1.87)
(−3.99)
(−5.00)
(−6.11)
0.297***
0.262***
0.591***
0.529***
(4.57)
(4.33)
(4.79)
(3.79)
0.055***
−0.045*
0.041
0.008
(2.62)
(−1.70)
(0.51)
(0.08)
0.343***
0.702***
0.267*
0.365**
(5.24)
(8.64)
(1.80)
(2.56)
0.243***
0.414***
0.245**
0.309***
(4.29)
(6.43)
(2.40)
(2.69)
0.843***
0.851***
0.846***
0.874***
(9.51)
(9.83)
(9.68)
(9.94)
−0.084
−0.090
−0.131*
−0.078
(−1.08)
(−1.19)
(−1.70)
(−1.04)
0.230***
0.225***
0.212***
0.222***
Zip code–level covariates
Percentage 25- to 34-year-olds (1990)
Percentage college graduates (1990)
Percentage nonwhite (1990)
Cultural industry cluster
Urbanity
Self-expression
Transgression
Self-expression × Transgression
Transgression (Neigh.)
Self-expression × Transgression (Neigh.)
County-level covariates
Population (1990)
Median gross rent (1990)
Percentage Democrat vote share (1992)
(4.73)
(4.76)
(4.37)
(4.64)
0.105**
0.107**
0.110**
0.117***
(2.35)
(2.39)
(2.46)
(2.68)
0.085**
0.085**
0.088***
0.085**
(2.42)
(2.45)
(2.59)
(2.50)
−0.174***
−0.178***
−0.215***
−0.165***
(−3.80)
(−4.03)
(−4.76)
(−3.76)
−3.378***
−3.443***
−3.472***
−3.509***
(−52.91)
(−56.04)
(−53.43)
(−54.72)
Level 2 variance
1.350
1.346
1.311
1.272
Level 1 variance
10.771
10.660
10.732
10.758
ρ (ICC)
0.111
0.112
0.109
0.106
N (counties)
2,625
2,625
2,625
2,625
N (zip codes)
24,465
24,465
24,465
24,465
Degrees of freedom
19
19
19
19
Log-likelihood
−64,670
−64,549
−64,610
−64,622
Crime rate (1999)
Employment ratio (1994–2001)
Natural amenities index
Constant
Note: This table extends table 8.8 by presenting results for multiple different catchment areas for measuring the
transgressive context surrounding a zip code. Bootstrapped t-statistics in parentheses (3,000 replications).
***p < 0.01
**p < 0.05
*p < 0.1
Catchment areas do matter. In particular, the R = 1 model exhibits stronger relationships
between our outcome and self-expression in the target zip code, transgressive scenes in the
neighboring zip codes, and their interaction. At the same time, the within–zip code
interaction between self-expression and transgression shifts from positive in the original
model to negative (and barely significant) in the R = 1 model, then insignificant in the R
=2 and R = 3 models. The R = 2 and R = 3 models exhibit their own patterns, where the
independent main effects of within–zip code self-expression and transgression become
increasingly important, but the effect of neighboring zip codes remains on par with the
original R = 0 model. That is, the impacts of local zip code scene qualities become even
more pronounced the more we take account of their surrounding scenes. These results all
add nuance to our initial finding: young people are drawn to transgressive scenes, not to
self-expressive scenes in isolation. But when self-expressive scenes are joined by
transgression nearby, they become more attractive to 25- to 34-year-olds. Proximity alters
performance.
In sum, both the scenes within zip codes and nearby surrounding scenes make a
difference for changes in the 25- to 34-year-old population. Scenes are localized
phenomena that operate within and across zip code boundaries. While exploratory, these
models collectively suggest that there are quantifiable boundaries to scenes and their
effects, with catchment areas of different radii transforming these effects. Pursuing these
lines of inquiry is an active area of ongoing research, which we illustrate here with this
initial analysis to show how it can deepen our understanding of some of the processes
identified in Scenescapes.
This “rings” method of analysis builds on a large geography literature on catchment
areas, with empirical estimates for certain very specific items, but clearly there are large
variations by amenity, activity, and subgroup (cowboys who drive 200 miles for dinner
versus Manhattan residents who don’t drive, the reach of opera houses versus that of a
coffee shop, etc.). One point here is simply that the specific tools and concepts of scenes
analyses help identify coherent patterns of variations, which can be joined with new data
as they emerge to better conceptualize and measure catchment areas. For example, adding
scenes indicators can distinguish between the effect of restaurants (alone) or restaurants
near a more transgressive scene, for separate age groups, and more.
These multiple approaches illustrate alternatives to modeling context. Results from OLS
models, HLM, interactions, catchment areas, and adjacency analyses each add insights.
Each makes different assumptions and employs different computational techniques.44
Despite these differences, we have been pleasantly surprised to discover that the simplest
possible multivariate modeling we performed also happened to be quite robust. More
involved methods produce more intricate pictures of the general relationships, which is
exactly what we would expect.
Scenes as Elements of Multicausal Processes
This book has mostly treated scenes as independent variables and other variables as
outcomes, such as economic growth, residential patterns, and partisan voting. We chose
this path in part because of the extreme complexity involved in evaluating any claim about
what causes a specific scene, and in part because we wanted to insert scenes into academic
and policy discussions about the drivers of income and job growth, residential patterns,
and partisan voting. This latter goal implied analyzing scenes as independent variables,
together with classic social science variables thought to drive these outcomes (education,
population, and the like) to minimize spuriousness.
In treating scenes as independent variables, Scenescapes may seem to resemble a sort of
“cultural sociology,” where “cultural” variables drive “material” outcomes.45 This is
misleading in that it is impossible to draw any hard-and-fast distinction between what is
cultural and what is material. More important, we are not dogmatic culturists—reversing
the equation is just as possible and plausible.
Being open to this reversal—considering scenes as either consequence or cause—
implies at least two further types of questions. First are the chicken-and-egg questions:
Which comes first, the scene, or other variables, like college graduates or jobs? Does one
always precede the other? Or does sometimes one, and sometimes the other, come first? If
so, when, where, and why? Questions more in line with much research and theorizing in
the sociology of culture come next: If we treat scenes as results of other factors, what
explains where and why one type of scene is stronger than another? Class, ethnicity,
religion, education, or something else entirely? That is, how can we bring our concepts
and data to bear on questions deriving from theories in which scenes are dependent rather
than independent variables? We briefly address both questions.
The Problem of Causality
Causality is a sensitive issue in all our lives. Max Weber even suggested stressing elective
affinities among variables rather than seeking causality. By the late twentieth century,
social scientists had often grown more ambitious about causality. Yet most accept Weber’s
fundamental ideas about multicausality, contingency, close interrelations among key
variables, and especially changes in all of these over time. Few rally around the
nineteenth-century flags of “culture” or “materiality” as the ultimate causes of social
processes “in the final analysis.” Most social scientists have accepted the interdependence
of many types of processes, the difficulties and arbitrariness of definitions, and the shifts
over time and within different contexts, all of which are compounded by feedback
effects.46 Thus feedback is one type of specific causal mechanism, which helps to clarify
what may look impenetrable at a distance.
One way to think about feedback is in terms of the chicken-and-egg problem. Which
comes first—the chicken or the egg? This labeling of the problem underlines the degree to
which, over time, each is essential (i.e., changes in one feed back and affect the other),
even if one seems primary at any specific point in time, and distinct causal dynamics can
be identified at multiple stages.
Scenes analysis is linked with the rising salience in many scientific domains of this
broader multicultural and multicausal perspective. It implies its own version of the
chicken-and-egg question. An example of one of its cruder forms is, Do locations with
more income attract more Starbucks, or do Starbucks attract persons with more income?
This is the starkest formulation of the problem, as sometimes discussed in the urban
literature.47
Our answer to “the Starbucks question” is that this is indeed a classic chicken-and-egg
phenomenon. In any one short time period a statistical analysis may suggest that the driver
is income but in a longer slice of time causality can reverse. How to interpret and measure
these processes?
The migration and urban development literatures have slowly but increasingly
recognized such interdependence over several decades. Clark and Ferguson’s (1983)
review of the migration and development literatures found only a handful of papers by
economists who had explored this chicken-and-egg question at the time. Richard Muth
and Michael Greenwood were key figures. They used cross-sectional analysis of job
growth and population growth for the entire United States, applying two-stage least
squares to estimate the relative impact of population growth on jobs and vice versa. They
found substantial impact both ways, but the strength of each was difficult to disentangle.
Given the many other associated variables, they did not try to explore this further.
Yet Clark and Ferguson suggested that, contra the general theories of Muth and
Greenwood, their results could be reinterpreted. Rather than trying to disentangle
production and consumption as separate or unidirectional causal arrows, they could be
seen as co-constituting each other. That is, people would choose a place to live as well as
work simultaneously. Moreover, this overlap was increasing as work itself became more
similar to a lifestyle decision about how to meaningfully spend one’s time, especially
among self-employed persons and highly skilled professionals. This general orientation
informs much of the analysis in Scenescapes: people select a location for many reasons,
including amenities, and once they are there, they contribute to the character of the place,
including its scenes.
These arguments have been developed substantially in subsequent years by ourselves
along with John Kain and his students, Edward Glaeser, Richard Florida, and others. This
is a relatively new interpretation. Much of the urban literature followed the so-called
economic materialist interpretation until relatively recently (as evidenced by the
widespread use of textbooks like those following the Muth tradition), which suggests that
factors like jobs are the primary drivers of people’s decisions about where to live. There
has been almost no serious research to extend the sort of studies initiated by Muth and
Greenwood perhaps because of the intrinsic complexities we flag here.48
Despite the relative lack of research progress, in discussions about scenes we are
frequently asked variations of this chicken-and-egg question. For example, does income
cause a scene to change, or vice versa? The first simple answer is that these are classic
processes throughout the social sciences and not specific to scenes. Thus the kinds of
logical answers, the methodology and data that are used elsewhere, can be applied here.
Some studies use cross-sectional data, others two or three periods, others large numbers of
time periods. So have we.
The second main answer is that given the huge complexity of factors that generate
scenes, for strategic reasons we have for the most part not sought to conceptualize and
measure their constitution in this book. Rather we have mostly focused on the
consequences of scenes for several widely used items in social science and policy
discussions (like population change, rent, patents) to help establish scenes impacts in the
same models as many others have developed.
Third, it is distinctly difficult to explore chicken-and-egg dynamics precisely. Since the
scenes data are so extensive and draw from so many sources, it is exceedingly difficult to
find comparable data across many years from all sources. Thus it is difficult to follow one
systematic pattern and consistent model to test simple hypotheses. The YP data were
collected at one time point only, since YP business directory services generally discard
their historic data and update their categorizations in ways they refuse to report (we
tried!). The US Census of Population is only completed every decade. The Economic
Census collects data every few years. The exception to this is the BIZZIP data set, which
is updated annually, but like (many, alas) other “series,” it changed coding schemes over
time, reducing the quality of analyses using performance scores that attempt to combine
data across time periods. Clearly, if we tried to make the sort of strong statistical and
econometric assumptions logically necessary for the stronger statistical procedures, the
data are too inconsistent to identify precise sequencing.
The Chicken and the Egg, Total Jobs and Arts Jobs
We investigated some distinct chicken-and-egg dynamics by examining arts jobs in
relation to other jobs, contrasting patterns across all US zip codes. We explored changes
over time and for selected subgroups of zip codes. We analyzed repeatedly mutual impacts
of arts jobs on total jobs of all sorts at the zip code level. The total jobs item simply
summed all jobs in all industries collected by the US Census of Business (BIZZIP), for
each US zip code. Unfortunately the codes for job categories changed, such that the older
Standard Industrial Classification (SIC) codes were replaced by a new set of NAICS
categories in the 1990s. Then the NAICS categories were revised. Thus, for longer time
periods, one confronts problems of consistency in classification.
We did many analyses using the data available for slightly different time periods. One
solution to the problem posed by changes in job classifications was to simply sum all jobs
in all categories to create a total jobs measure; for this, the definitions of job categories
should be irrelevant. Then we looked at the subcategories of arts jobs and found that most
subcategories were repeated with near identical labels from the 1980s until after 2000.
Thus it seemed reasonable to estimate the impact (economic elasticity) of arts jobs on total
jobs over the years from the 1980s to after 2000. This seemed important as one of our
findings was that arts jobs were one of the most powerful predictors of job growth after
2000, even when controlling for our core variables. We wanted to see if this same strong
relationship between arts jobs and (subsequent) growth in total jobs held over time—
especially as there is virtually no systematic comparative analysis in the small literature on
arts jobs as drivers of urban growth, and virtually none that confronts chicken-and-egg
issues.
One interesting finding was that in the earlier years, 1980s and 1990s, arts jobs did not
have a significant impact or relationship to growth in total jobs in subsequent years. But
from 1998 to 2001, the arts job impact was strong, the strongest of all variables in a 10variable model. We could not use data for each subperiod for all our other variables due to
data availability, so these results are tentative.
Nevertheless the apparent rise in impact of arts jobs on general job growth over time is
consistent with our more general interpretation that as a general indicator of
consumption/lifestyle spaces, and specifically more self-expressively oriented scenesrelated amenities, arts jobs may have increased in importance in the last few decades.
These results fit with our discussions of shifts in a postindustrial society toward
consumption and amenities as distinct opportunities to express personal values and styles
of life. These last statements are based on assessment of many different sources of
evidence in addition to those originally analyzed here, but the rise in the specific arts job
to total job elasticity fits with the broader interpretation.
Cross-lagged regression permits further analysis of the relationships of total jobs and
arts jobs. Figure 8.4 illustrates the general cross-lagged regression approach. We use this
method as it takes advantage of the annual BIZZIP data for the large number of zip codes.
The basic idea of cross-lagged regression is to allow for an analysis across different time
periods, using data that is normally analyzed cross-sectionally. In our case, we analyze
how much arts jobs influence total jobs, after we (statistically) remove the impact of total
jobs from earlier years. The top and bottom horizontal lines in figure 8.4 are thus mostly
“controls” of the same variable across time, while the two diagonal lines are the key items
to contrast. The beta coefficients for the crossed lines show the relative impact of arts jobs
compared to other (nonarts) jobs in explaining the change from 1998 to 2013. We
explored many variations of this basic model, adding further variables, interaction terms,
and so on. But the main results held strong.
Figure 8.4 Cross-lagged regression, general model
The individual variables are simply levels of absolute numbers (not change or per capita). By including the absolute
number of arts jobs in a zip code as both independent and dependent variables in the first equation, the first beta (with
the subscript “lagged”) shows the direction and magnitude of change (growth or decline) in arts jobs from 1998 to 2013
for all US zip codes. The method does not require the strong assumptions demanded by other methods, such as
“instrumental variables” in two-stage least squares regression.
A first analysis contrasted the diagonal coefficients (as in figure 8.4) and found them
both significant, for changes in arts jobs and nonarts jobs from 1998 to 2013. This differs
from earlier years when there was zero impact of arts jobs on later numbers of total jobs.
Our second analysis compared the relative impact of arts jobs in different types of zip
codes. We hypothesized that there may be a stronger taste for the arts and often more
diversification in locations with larger populations, and more educated and affluent
residents. In such locations, arts jobs may have higher impacts (elasticities and multiplier
effects) on the numbers of nonarts jobs in subsequent years. To test these simple
hypotheses, we contrasted the impact of arts jobs in zip codes that varied in population,
education, and income (see the note to figure 8.5). We found support for the hypotheses.
The results depicted in figure 8.5 show that arts jobs spark other nonarts jobs more in the
top 10 percent of zip codes in population, education, and income. By contrast, arts jobs
have relatively weaker impact over time on nonarts jobs where population size, education,
and income are lower. The other (nonarts) jobs show more impact on arts jobs and other
jobs in locations in the bottom 10 percent. For all zip codes, by contrast, results were in
between the top and bottom groups, as expected.
Figure 8.5 The impact of arts jobs on job growth varies across zip codes
The paths shown here are only the diagonal paths from the full model we estimated, shown in figure 8.4. We reestimated
the full model three times for three sets of zip codes; the high and low 10 percent are summarized in the two sets of paths
shown above. The high and low 10 percent were from an index of three items for all US zip codes: median household
income, percentage residents with a BA or higher degree, and surrounding county population. The top 10 percent on all
three items included 1,421 zip codes and the bottom 10 percent was 1,076 zip codes. The figure contrasts betas for the
high and low zip codes; results for all US zip codes were in between in the cross-lagged regressions. The thickness of the
arrows illustrates the relative strength of the relationships. For instance, in the top 10 percent, the impact of (1998) arts
jobs on (2013) total jobs was greater than the impact of (1998) total jobs on (2013) arts jobs.
In sum, arts jobs do drive economic growth. Zip codes with more arts jobs often grow
all kinds of jobs faster. This arts multiplier effect is largest in zip codes with higher
population size, education, and income. So we find a chicken-and-egg pattern, but the
magnitude of each effect varies by type of area. There is no general answer to the question
about which comes first, arts jobs or total jobs, in the final analysis. Each feeds into the
other. But arts jobs enhance local scenes and often encourage more general job growth.
The chicken-and-egg metaphor is useful for many complex social phenomena, scenes
and others: it is futile, the metaphor suggests, to seek first causes or prime movers. Rather,
if change in one factor occurs, in a highly interdependent system, it brings consequences
that feed back on other factors in the next time period. And so on. Sometimes one factor
leads and others follow; next it may be the other way around. Sometimes one can be more
precise about specifics, such as how variables such as population, education, and income
shift the impacts of arts jobs. But why seek to overgeneralize? We need both chickens and
eggs.49
Scenes as Dependent Variables
That scenes are part of complex feedback mechanisms implies that it makes sense to
analyze them as dependent variables and not only as independent variables, testing
theories about not only the consequences but also the sources of scenes. Reversing in this
way the typical approach of Scenescapes brings us immediately into closer conversation
with studies more characteristic of “the sociology of culture.” Here one investigates, for
instance, why one type of cultural practice, taste, sensibility is more likely to occur in a
given place or group than another.
Many leading theories of culture in the social sciences work in this explanatory
direction, with “cultural variables” as outcomes. In a similar way, throughout Scenescapes,
we have often noted that many processes we consider can also be analyzed from this
perspective. For instance, a neighborhood with a self-expressive scene may attract college
graduates; but at an earlier point, the emergence of this scene may have been encouraged
by college graduates as customers and residents. We have accordingly explored potential
explanations for why some scenes are stronger or weaker in different places, in reference
to leading theories from the sociology of culture.
Here as in the rest of Scenescapes, we begin with key variables posed by others to
assess their impacts, in this case on our scene variables. A first example is a general
proposition in the mode of Pierre Bourdieu or Thorstein Veblen—that class inequality and
segregation should strongly determine differences in style and taste. This has been widely
discussed in past literature. In Veblen’s version, elites undertake lavish and conspicuous
consumption not for any physical need but to display their dominant social position and to
inspire “pecuniary emulation” in others. In Bourdieu’s variant, high culture provides a
suite of special knowledge, manners, and tastes that helps those at the top of the social
hierarchy distinguish themselves from, and thereby exclude, those below.
We examined both of these claims separately but focus here on the more Veblenesque
version.50 To do so, we used a measure of metropolitan income segregation from John
Logan, a leading researcher on the topic, the “the rank-order information theory index
H.”51 We then analyze the connection between income segregation and the five factor
score combinations of scene dimensions from chapter 5: Communitarianism/Urbanity,
LA-LA Land, Rossini’s Tour, City on a Hill, and Nerdistan. These focus on Veblenesque
conspicuousness included in more flashy consumption styles, like glamour and exhibition,
especially LA-LA Land.52
If we look first at simple bivariate Pearson correlations between metro income
segregation and the five factor scores, we find that four out of five scenes are positively
correlated with metro inequality (all but egalitarian City on a Hill). But if we add only
three more variables (specifically metro total population along with zip code education
and rent, since these types of variables are widely discussed in several overlapping
literatures as major social drivers of differences in cultural tastes), the picture changes, as
table 8.11 shows.
Table 8.11. The relationship between metropolitan income segregation and scenes
becomes insignificant or reverses after adjusting for other variables
Relationship with
metropolitan income
segregation, adjusting
for four variables
Communitarian vs. Urbanity
0
LA-LA Land
0
Rossini’s Tour
−
City on a Hill
0
Nerdistan
+
Note: This table shows the relationship between five scenes and metropolitan segregation, after we adjust for the metro
total population, zip code rent, and zip code education. All five scenes are positively correlated with inequality in a
simple bivariate relationship. After adding the other variables, three become insignificant and one shifts from positive
to negative. Only Nerdistan remains positive. These scene variables are derived from factor analysis of the 15
dimensions. Factor weights for each dimension in the five scenes are summarized above, in table 8.4, and the factors
are described in more detail in chapter 5.
Table 8.11 summarizes relationships between the five factor scores and metro income
segregation, after we include the other variables. It makes immediately clear how much
the simple bivariate relationship with metro inequality leaves out. When we add these
three basic controls, the positive relationship between metro inequality and the scenes
either disappears or reverses sign.
Most notably, the link between metro inequality and LA-LA Land—perhaps our most
conspicuous-consumption-oriented scene, in stressing glamour and exhibitionism—
becomes insignificant, as does the association between metro inequality and
Communitarianism/Urbanity. Rossini’s Tour, which combines local authenticity and selfexpression, we now see, is typically found in less segregated metros once we adjust for
these other variables. The negative association of inequality with City on a Hill has also
become insignificant. The only scene to be positively linked with metro inequality is
Nerdistan (Nerdistan is a complex scene stressing formality and rationality [see table 8.4],
all weak measures of conspicuousness compared to glamour and exhibitionism). The
Veblenesque theory—that variation in scenes should be traceable to variation in residential
income segregation—does not find much support in these results. It may well be that
Veblenesque ideas hold in some scenes for some groups of persons, and maybe more in
the past or other countries, but they do not emerge readily or strongly here.
The general methodological point here is that many plausible and standard variables are
starting points rather than stopping points for investigating the sources of scenes—we can
begin with Veblen but cannot end there. Indeed, the variables in the models summarized in
table 8.11 only account for a small amount of the variance in the scenescape: the adjusted
R-squared for Nerdistan is the highest, around 0.14, and the rest are 0.1 or below. Pursuing
other potential explanations, such as ethnicity, occupation, region, and much more, and
slowly folding them into leading theories in the sociology of culture, is thus an active area
of current scenes research.
Scenes in International Context
Scenescapes has mostly described and analyzed the American scenescape, sprinkling
illustrative references to other countries throughout, and including somewhat more from
our neighbor to the north, Canada, where our lead author is based. But scenes research is a
truly international endeavor. Teams in Canada, France, Spain, Poland, Japan, Korea, and
China are studying their countries’ scenes. These international efforts are exciting
opportunities to extend, revise, and test the approach in Scenescapes, as well as
challenging occasions to work out new ideas and methods for comparing and analyzing
scenes cross-nationally.
Clemente Navarro’s team in Seville’s Universidad Pablo de Olavide has been an
international leader in scenes research (see, for example, Navarro 2012). This is not
surprising given Navarro’s crucial role in developing many scenes concepts and methods.
Navarro and colleagues built a database of Spanish amenities similar to our own, applied
the same type of scoring system, and computed performance scores for approximately 800
localities. Exploratory factor analysis of their performance scores reveals a first factor
similar to the first factors in US and Canadian performance scores—Navarro and
colleagues call it “conventional vs. unconventional,” with dimensions like neighborliness,
locality, and tradition on one side and transgression, self-expression, and glamour on the
other. And they have mapped this factor across all of Spain, revealing a strong
concentration of “unconventional” scenes in the Northeast and around major cities, as in
figure 8.6.
Figure 8.6
This map plots the relative Communitarianism versus Urbanity within Spain’s scenes. Darker is more Urbane. Source:
Figure 2 (p. 309) from Clemente J. Navarro, Cristina Mateos, and Maria J. Rodriguez, “Cultural Scenes, the Creative
Class and Development in Spanish Municipalities,” European Urban and Regional Studies 2, 3 (2014): 301–17.
Building on these scenes measures, Navarro and colleagues show that the
unconventionality versus conventionality of the scene is a strong predictor of where
Spain’s “creative class” is located. Moreover, unconventional scenes are strongly linked
with higher relative incomes in Spanish localities and in fact enhance the connection
between “the creative class” and income, which is also strong. These results are especially
important in the European context, as they, together with other recent European work on
amenities,53 provide grounds for doubting the claim that the links between scenes and
economic growth are dependent on parochial features of North American countries, such
as (sometimes) higher geographic mobility. Some of the Navarro team’s results are in
Navarro, Mateos, and Rodríguez (2012).
Teams in France and Korea have created similar maps. In Paris, Stephen Sawyer’s
(2011) group charted Parisian scenes, as a way to better understand the on-the-ground
cultural styles that strongly differentiate Parisian neighborhoods. Using yellow pages and
census data similar to ours, they mapped all Paris area communes and arrondissements,
not only across all 15 dimensions, but also on combinations that capture key Parisian
scenes, like “the art of living” and “the underground,” extending our initial approach to
detecting scenes to capture some of the specific context of French culture (Clark and
Sawyer 2009–2010). Work continues in all French communes.
Wonho Jang in Seoul led a team that produced two reports, mapping Seoul’s scenes and
comparing them to scenes in Tokyo and Chicago. Others are pursuing comparable work,
often with methods and data similar to those employed in Scenescapes, sometimes
exploring new techniques, as in Chad Anderson’s studies of scenes in Seoul and China
using photo ethnography. Links to much of this ongoing work can be found on our
website.
In China, Wu (2013) analyzed 374 districts in 35 large Chinese cities. He and
colleagues coded amenities using the basic 15 scenes dimensions and factor analyzed
them. They found interesting age differences across neighborhoods. Areas with older
residents more often featured state, corporate, and utilitarian dimensions, while those with
younger residents featured more exhibitionism, self-expression, and charisma. He
completed geographically weighted regressions and network analyses among amenities,
which detailed how these differences affected rent prices across neighborhoods.
Jang, Clark, and Byun (2011) is especially important in the present context. It breaks
new ground by explicitly comparing scenes cross-nationally, finding intriguing differences
in conceptions of Bohemia—a concept unfamiliar to most Korean and Chinese social
scientists and intellectuals. This led Jang et al. to deconstruct the concept of Bohemia into
10 distinct components and look for parallels in each cross-nationally. In this way
Bohemian components were isolated and compared, showing different spatial distributions
of Bohemian scenes in Seoul, Tokyo, and Chicago. Chicago shows more neighborhood
segregation in such scenes; zoning is weaker in Tokyo and Seoul. The report also shows
Asian challenges to the Tocqueville/Putnam proposition that civic participation generates
trust in politics.
These differences raise important substantive questions about how and why
Bohemianism, civic participation, and citizenship in Asia differ from their European and
North American variants. But they also point toward the more general emerging frontier of
scenes research coalescing around the comparison of scenes across nations. That is, rather
than labeling a pattern by its nation or region like Asia, it leads us to drill down to identify
counterparts to “Asian” patterns in the West, using more generalizable concepts like
family strength, social integration, and the like. Then by comparing combinations of
scenes dimensions we can show how patterns that may seem to be “Korean” recur in
Western areas with stronger families, more local social integration, and other related
components. Reanalyzed in Asia, our Gemeinschaft/Gesellschaft factor that looked quite
similar in Spain captures elements that both differ and help interpret some Asian/Western
differences (Jang, Clark, and Byun 2011). These international comparisons of democracy
and development are extended via arts and culture in Clark (2007, 2014).
Methodological Challenges of International Scenes Research
Cross-national scenes research poses its own methodological challenges. A first challenge,
seemingly trivial but in fact quite difficult, is simply merging and/or comparing data from
so many sources, compiled in different languages, at different units of analysis. An initial
international scenes database has been created (led by James Murdoch), but cross-national
analysis is just beginning by the teams who contributed the basic data (from Spain,
France, Korea, and more).
A potentially deeper challenge is the question of what exactly to compare and how. One
option is to focus on a small subset of amenities for which data are available in many
countries, like museums and restaurants and religious organizations. This restricted set of
amenities could be used to calculate performance scores across countries in two relatively
straightforward ways. One could then use the original US coding of amenities’ scenic
meaning (e.g., to gain insight into how Americans would view the scenes in Germany). Or
local teams could apply their own coding system (e.g., to gain insight into the
relationships explored in Scenescapes within Germany). It is illuminating to do both and
compare the results.
Another option is for national teams to collect whatever amenities data they believe best
capture the character of their countries’ scenes, based on their local expertise, again either
applying the US coding or their own. As we found that our approach to calculating
performance scores minimized the effect of adding or removing individual amenities, we
can see if this robustness holds true in other contexts, allowing other researchers to use
their own judgment in terms of what constitutes the most informative amenities for
inclusion. Further, teams could pose additional scene dimensions (as Stephen Sawyer has
in France or Silver has in Canada), to capture ideal typical scenes that our US-based
approach has missed, or discard dimensions that seem less salient. This flexibility is one
of the most powerful aspects of our science of scenes.
Given potential variation in the meaning attributable to amenities, and even the scene
dimensions they constitute, studying combinations of scenes such as via exploratory factor
analysis becomes distinctly useful for international comparisons. All scenes are measured
imperfectly, and cross-nationally even the meaning and/or makeup of our scene
dimensions can vary.
Indeed, the possible existence of relatively consistent configurations of scenes crossnationally opens up tantalizing directions for future research that make the world a smaller
place culturally. There was no a priori reason why a similar factor number 1 should exist
among scenes in the United States, Canada, Spain, and China. In fact, there is ample
reason to believe that Spain should be more culturally dissimilar to North America than
similar. Yet early results taking this approach are promising. For instance, the similarities
in the first factors in the United States, Canada, and Spain suggest strong cross-national
commonalities but at the same time reveal subtle differences as well.54 Then to find larger
differences in Korea, for instance, is a step toward more precisely interpreting what
“Asian” or “Korean” means in more generalizable, but precise, components.
Comparing the correlations of various scene dimensions with rent is also intriguing.
Toronto and Montreal stand out in that their more formal scenes have higher rent, whereas
in most other cities and countries, glamour and self-expression have higher rent. We
would also expect some strikingly different national meanings of amenities to emerge
through their different spatial distributions and relationships to other amenities (like the
strong differences in the location of churches in France and the United States, noted in
chapter 3). Further, comparing what constitutes a transgressive scene in the United States
versus, for instance, Korea provides significant insight into larger cultural differences that
are often lost in translation and therefore difficult to pinpoint.
We also stress that scenes analysis can inform many different overlapping theories, data,
and methods, from multiuse and New Urbanism concepts to video and photo essays to the
ethnographic to the historical to the architectural and more. Conferences and publications
on scenes are multiplying in several disciplines and countries. We look forward to more.
The primary aim of this chapter was to provide an overview of our multiple ways of
constructing a science of scenes. It builds on chapters 2 and 3 to summarize in more detail
how we measured our core concepts and overviews the main analytical procedures
employed throughout the book. We used many data sources and methods to assure
ourselves and our readers that the key relations were being tested systematically, defined
by adapting the best data and methods we could find in related fields and disciplines. The
main strategy was to identify a core set of variables used in past work and to add our
scenes measures to models used by others. “Systematically” here means seeking to assure
ourselves that scenes are significant by specifying how they combine or complement other
variables, like education and residential choice. This largely means measuring the size of
scenes effects compared to other variables, assuring that they are not spurious, and
detailing how relations among variables like education and voting vary by context.
Our more original contribution is to codify procedures for capturing and analyzing
scenes. Our performance scores quantify the salience of each of our 15 scenes dimensions
indicated by the amenities in that zip code. These measures provide a powerful way to
capture the range and combinations of cultural meanings present across different localities
and to integrate cultural analysis into comparative and quantitative studies of urban
development. They bring the scene within the purview of a social scientific account of
how and why our cities and communities are changing.
Notes
Chapter One
1. See Small, Jacobs, and Massengill (2008) and Small and McDermott (2006).
Chapter Two
1. Martin instead develops the idea, drawn from Pierre Bourdieu and others, of “the field” as a way to explore the
“configuration of a local situation” (2011, 77). Situations come in “clumps” of related activities and practices, and
“people then rearrange those clumps in larger heaps to suit their practical needs” (144) “Field” is one of many
recent concepts intended to permit a more flexible study of culture in its local variations.
Chapter Three
1. As new, web-based “big data” sources become available (e.g., Facebook, Yelp, Twitter), new potentials for rich
and more precise measurements of scenes are emerging, which we are exploring.
2. That is, to an American this may not be shocking, that is. But to someone from France it might be. In fact, in our
exploratory research into French amenities data, one of the most striking differences between France and the
United States is the location of churches. In America, they are nearly everywhere, from small towns to big cities,
from storefronts in inner-city low-income African American and Hispanic communities to suburban
megachurches. But in France, they are nearly all in the major city centers and along the main boulevards, and
nowhere else—symbols of a historic and grand national center rather than a local neighborhood or active spiritual
entrepreneur.
3. The ethnic bases of Chicago, Los Angeles, and New York provide one obvious source for these distinctions. Jews
and reform Protestants were more numerous in New York. Their religious traditions resonated more with Marxist
themes. A divine-inspired journey toward abstract, universal justice was a leitmotif. It was simultaneously an
attack on competing subcultures, like the strident individualism of the Wall Street market or the selfish
pawnbroker. Ideological debates were heightened by the weakness of government and political parties, plus the
higher density of national media and publishing firms. By contrast, Chicago politics in the twentieth century was
marked by an Irish ethic of nonideological particularism, specifically localism, social conservatism, practicing
Catholicism, and sociability (Clark [1975] reports extensive survey and historical data supporting these ethnic
differences): “Don’t make no waves, don’t back no losers”; “You deliver your ward, I’ll deliver mine.” New York
is the polar opposite on all these dimensions, with global and national rather than local aspirations, strident social
liberalism, aggressive secular ethics, and ideological engagement in public life. The New York Times is the most
obvious illustration and carrier of this outlook to New York–centric locations across the United States. See AbuLughod (1999) and McNickle (1993) for more specifics.
4. Chicago and New York long had local political party organizations that welcomed immigrants. Los Angeles by
contrast has been marked by more white protestant domination and ethnic conflict, from the Chandler family of
the LA Times, to the LA riots in 1992, to referenda against immigrants and abolishing affirmative action
(statewide), to Mexican and African American gang warfare—themes stressed by LA scholars like Davis (1990),
Sonenshein (1993), and Ethington (2015).
5. See Glaeser, Kolko, and Saiz (2001); Papachristos, Smith, Scherer, and Fugerio (2011); Falck, Fritsch, and
Heblich (2010); and Reese, Faist, and Sands (2010).
6. Because a strong ethnic authenticity performance score is based solely on the amenities in a zip code (and mostly
restaurants, among YP amenities), it does not necessarily indicate a more traditionally defined ethnic
neighborhood, which we might define as including both certain types of amenities and residents from a distinct
ethnic background. Looking at correlations of residents’ ancestries and amenities helps to measure this more
traditional ethnic neighborhood. If we do so, we find, for instance, that in Chicago people of Italian and Irish
ancestry are more likely to live in zip codes with Italian and Irish restaurants (respectively) than they are in New
York. Still, there are many possible ways in which amenities and residents can overlap, even in the same city.
Hackworth and Rekers (2005) show several possibilities in Toronto: Little Italy, with many Italian restaurants not
owned and operated by Italian-Canadians and few Italian-Canadian residents; Greektown, with a declining nearby
Greek-Canadian population but many businesses owned and operated by people of Greek ancestry, which host
many other Greek-Canadians who come there to eat and socialize at night and on weekends; Little India, which
never had a decline in Indian-Canadian population, because few Indian-Canadians lived there from the start—it
was always more a commercial than residential district.
7. Chapter 8 explores how more advanced statistical techniques can be used to model spatial context as well.
8. Vancouver shows another pattern, often with high citywide averages but fewer extremes, a pattern that also
appears in studies of artist concentrations, where Vancouver typically has the highest average for the whole city,
but Montreal and Toronto have individual neighborhoods with higher concentrations.
9. This cultural legacy appears in at least two further ways in our data. First, Toronto’s average transgression score is
below the national mean, the only major city in the United States and Canada we have analyzed for which this is
the case. And formality is in general, as we have found in our preliminary international comparisons, much more
strongly linked with high rent in Canada than in the United States—“Canada the Exhibitionistic” does not exactly
roll off the tongue. Second, we see differences in specific amenities associated with “alternative” lifestyle. In
Toronto, there are more amenities that support earnest personal development in marginal or specialized practices
like yoga, meditation, used bookstores, and natural healing centers; in Montreal, there are more visual, bodyfeaturing amenities like sex shops, leather stores, discos, and modeling agencies. Toronto’s alternative scene is
more Bohemian; Montreal’s is more dandyish. The general methodological point here is that the scenes measures
are not meant to be abstract context-free indicators but instead invitations to compare one place to another along
common themes.
10. We derive these combinations by factor analysis; specific weightings of each dimension on each factor are in
chapter 8. The most common combination of dimensions in Canada is similar in general but intriguingly different
in specifics. It divides the country between a kind of functionalist core—formal, utilitarian, rational, corporate—
and then “everything else,” including both more communal and particular (neighborly, traditional, ethnic, etc.)
and more fluid (self-expressive, glamourous, transgressive). Following Weber, we call this Canadian pattern the
“Steel Shell.” It may be encouraged by the fact that a higher percentage of Canadians than Americans live in
urban contexts, so the city versus country split itself is less decisive. While some of the other Canadian
combinations are also very similar to their American counterparts, the Canadian scenescape also contains one
lacking in the United States, strongly defined by statehood and rationalism, which we call La République.
Chapter Four
1. With Ricardo, as with any classical thinker, there are warring schools of interpretation. Following pointers in
Marx’s Theories of Surplus Value, the Marxian tradition has treated Ricardo’s theory of rent as basically Marxism
avant la lettre. On this view, when Ricardo says that rents are determined, in the last analysis, by comparing land
for which one must pay a rent to inferior soil that one could use rent-free, he is trying to show how, again in the
final analysis, all value comes from labor. This makes it a short step to Marx’s labor theory of value, in which,
because all value comes from labor, any proceeds that go elsewhere are inherently exploitative. Marshall (1892) is
perhaps the classical source for an alternative interpretation, according to which Ricardo was not an exponent of a
labor theory of value but instead gave due weight both to other factors of production and to the role of demand.
2. Jäger (2003) reviews much of the Marxian literature on land and rent, as does Emsley (1998) (in pursuing the
difficult distinction between “absolute” and “differential” rent). For a recent effort at extending and reinterpreting
a Marxian point of view, see Harvey’s (2009) “The Art of Rent,” which in some respects points in similar
directions to the present chapter in emphasizing the role of culture and the arts in generating distinctive local
value.
3. Thanks to John Paul Rollert for helpful discussions on this topic.
4. .See also Howard and King (1985, 147–48).
5. See Harvey (1982, 352).
6. Talcott Parsons’s comment on Marx’s dichotomizing bent is apt: “Marx seems to have been so dominated by the
‘logic of dichotomies’ that he over-hastily assumed that the triumph of the bourgeoisie meant ipso facto the virtual
elimination of aristocracy. . . . [The European aristocracy], though highly involved with the system of
ownership . . . was . . . much more than simply an owning-exploiting class in the Marxian sense. For example, it
was the primary sponsor, after its heyday of political ascendency, of the main cultural developments in Western
society. . . . In retrospect, neither of the Marxian capitalistic classes has actually been emancipated from the
‘feudal’ background, especially in Europe. The bourgeoisie are, as it were, in part frustrated aristocrats, and the
proletarians, frustrated peasants” ([1937] 1967, 111–13).
7. There is a somewhat subterranean tradition in modern economics devoted to studying land values and amenities,
exemplified most recently in the work of Albouy, Leibovici, and Warman (2013), who builds on Roback, Rausch,
Glaeser, and others. We have drawn much from this literature, and seek to extend it, in at least two ways. First, as
we have stressed in previous chapters, we go beyond the atomism of conventional economics by analyzing not
only individual amenities but scenes. Second, we are interested in what “amenability” consists in, how it is
produced and generated. Both directions are implicit in Albouy and Lue (2014), who write about how their
analysis of the land value generated by individual restaurants is “likely influenced by other retail and
entertainment establishments, neighborhood atmosphere . . . and the characteristics of local residents.” They also
note: “We lack a theory of amenity production.” Our scenes approach is an effort to make these two issues explicit
rather than implicit topics of investigation.
8. Specifically, this variable is constructed as a zip code location quotient that compares the percentage of jobs in
culture and related industries to the national percentage (detailed in the online appendix found at
www.press.uchicago.edu/sites/scenescapes).
9. Many of these expanded analyses are reported by Silver, Clark, and Graziul (2011).
10. We also analyzed the three types of patents, entertainment, high-tech, and other, and found mixed results for the
interaction term for self-expression and tech clusters: no relationship with entertainment patents, and negative
relationship with high-tech and other patents.
11. Of course, one might think that the relationship runs the other way, that scenes only become self-expressive in
response to the lifestyle preferences of tech workers. However, this does not seem to be the case: if we make selfexpression the dependent variable and analyze an array of factors that might predict self-expressive scenes, tech
clusters have little to no relation with self-expression (the strongest links are with artists and college graduates).
That is, self-expressive scenes are not generally the outcome of tech clusters; but if a tech cluster is located in a
self-expressive scene, it tends to thrive. Still, fully probing this classic chicken-and-egg problem is best done with
over-time data. We analyze this issue in chapter 8, asking which comes first from year to year, rises in artists or
rises in jobs. The general answer is that there is no general answer: sometimes one comes first, sometimes the
other.
12. More specifically, it is a factor score from a principal component analysis (with Oblimin rotation) of Canadian
performance scores, in which glamour, charisma, formality, self-expression (as well as natural authenticity) load
positively, and utilitarianism and corporateness load (moderately) negatively. Details on factor weights are in
chapter 8.
13. Some further specifications of the variables in figure 4.2 may be in order. “Professionals in art and culture” are
defined by Statistics Canada as librarians; conservators and curators; archivists; authors and writers; editors;
journalists; professional occupations in public relations and communications; translators, terminologists, and
interpreters; producers, directors, choreographers, and related occupations; conductors, composers, and arrangers;
musicians and singers; dancers; actors and comedians; and painters, sculptors, and other visual artists. The
creative class was defined by selecting Canadian National Occupation Classifications (NOC) codes that
approximate the specifications in the appendix to Florida (2002). These include professional occupations in
natural and applied sciences; professional occupations in health; judges; lawyers; psychologists; social workers;
ministers of religion, and policy and program officers; teachers and professors; professional occupations in art and
culture; technical occupations in art, culture, recreation and sport; senior management occupations, specialist
managers; managers in retail trade, food, and accommodation services; other managers; professional occupations
in business and finance; finance and insurance administration occupations; technical occupations related to natural
and applied sciences; nurse supervisors and registered nurses; and technical and related occupations in health.
14. We explored 2010 census data with similar models and found that the growth impacts of self-expression and
glamour persisted, though they were slightly weaker than 1990–2000. Both glamour and self-expression show
strong links with overall population and college graduate gains, while self-expression in particular was associated
with relatively strong rent and job growth (this latter association holds for the decade as a whole but is strongest
from 2000 to 2007). We also explored a longer, 20-year view, of growth in population, income, rent, and college
graduates over the entire period from 1990 to 2010. Self-expression was strongly associated with higher rates for
all four outcomes; glamour, with all but income growth.
15. By contrast, if we look instead at places with the most total fine artists, cafes, used bookstores, music stores,
nightclubs, tattoo parlors, antiques and collectibles, body piercing studios, and used clothing shops (that is, at an
additive index of these “Bohemian” amenities), then we see, along with a strong correlation with arts jobs, a
stronger correlation with utilitarian and corporate dimensions and technology jobs (a more “neo” Bohemian
scene, perhaps).
16. The association of the Bohemia and county Communitarianism interaction with college graduate change was
similarly insignificant (as was the main effect), while its association with other patents was negative, as it was for
entertainment and high-tech patents.
17. A Neo-Bohemian index (described in note 15 above, as the sum of several Bohemian amenities) shows a
somewhat similar pattern in that the less urbane the surrounding county, the more strongly Neo-Bohemian
amenities are associated with job and population growth.
18. This imputation of lifestyle characteristics is not unfounded. To validate it, we analyzed differences in
consumption behavior and attitudes between college graduates and postgraduates in the DDB survey. Generally,
postgraduates are more square; college graduates party more: college grads are more likely than postgrads to go
out to bars, say they enjoy “parties, games, anything for fun,” and have a younger ideal age. Postgrads are more
likely to have recently finished reading a book, collect rocks and stamps, spend time at a public library, attend
dinner parties, do community work, and say they have “somewhat old-fashioned tastes.”
19. Detailing these policies and linkages has not been done by anyone systematically, to our knowledge. They
clearly touch on issues of artist-led gentrification, to which we return in chapter 5.
20. “Walkability” here is the ratio of the number of individuals 16 years and older who walk to work to the total
population. We created and analyzed several other measures of social density: travel time to work, percentage of
the population working at home and walking to work, public transport use and population density, reported by
Silver, Clark, and Graziul (2011).
21. In addition to the USDA index of natural amenities, we explored (in Silver, Clark, and Graziul [2011]) other
variables measuring the impact of nature in urban development: average January temperature, average July
temperature, an index of waterfront amenities from our amenities database, using places with lakes, rivers, and
oceans as well as marinas, beach accessories, boat charters, river trips and tours, and waterfront food service.
Chapter Five
1. See Cortright (2005).
2. See Clark, Silver, and Sawyer (2015).
3. See Clark (2011b).
4. However, the relationships vary in intriguing ways within different cities and regions; they are particularly strong
for all groups in Chicago and San Francisco, for example.
5. While even these claims are based in specific neighborhood experiences, they lead their proponents to neglect
subtle explorations of different neighborhoods and suburbs, and the diverse scenes they create, on the grounds that
such subtle differences are illusory. Dear (2001) takes a generally strong position on these issues as LA School
spokesman.
6. See Clark’s forthcoming Trees and Real Violins for more on the general transition from Daley I to Daley II.
7. We explore this aspect of the new Chicago in more detail in Grodach and Silver (2012, ch. 2).
8. The phrase “blue-collar Bobos” comes from an excellent student paper by Vincent Arrigo and John Thompson
(2007) on the Bridgeport scene.
9. See Clark (2011c).
10. E.g., Kilson (2001).
11. William Julius Wilson’s and Orlando Patterson’s students have conducted some of the leading work on African
American neighborhoods and institutions. A hot continuing policy issue is what factors strengthen or weaken the
family. In the 1970s, the African American family was seen as distinctly troubled, as the proportion of children
with single mothers continued rising. But as the proportion of non–African American single mother families
increased, “family values” became part of the national political agenda, ironically perhaps under President Bill
Clinton, whose second election campaign stressed that theme.
12. See Small, Harding, and Lamont (2010).
13. See the work of Omar McRoberts (2003), Mario Small (2004), and David Harding (2010; Small, Harding, and
Lamont 2010) on these and related issues. The connection of scenes to local amenities clearly dovetails with this
recent research into what is often called neighborhood effects, particularly relating to the types of neighborhood
environments that support strong families. Across all US zip codes, our scenes measures fit with the standard
census items as expected: neighborliness in particular is stronger in neighborhoods with more children and
married couples. Local authenticity and self-expression are linked with married couples but fewer children, which
likely reflects the fact that these dimensions are also linked with baby boomers and college graduates.
Transgressive scenes have few children and fewer married couples.
14. These types of lifestyle aspirations are only loosely correlated with class, ethnicity, or education. There are
square and swinger college grads, rich people who go to pottery classes and rich people who take golf lessons.
Indeed, when we analyze individuals in the DDB lifestyle survey, we find that typically the correlation of race,
income, and education with any given type of consumption (going to the movies, golfing, attending pop concerts,
fishing, etc.) is not more than 0.3. That is, only about 10 percent of the variation in consumption behavior is
explained by race, or income, or education (0.3 × 0.3 = less than 10 percent).
15. Clearly the causality also runs the other way, even if according to a somewhat different logic and pace (residents
may build, or inspire entrepreneurs and politicians to build, near scenes consistent with their tastes, which often is
a piecemeal process that takes decades to unfold, and can veer off in numerous directions in different contexts).
Chapter 8 includes some further work justifying this approach, and going some way toward showing, as far as we
can with the data we have, where and when changes in people precede changes in scenes, and vice versa. Where
we do have longitudinal data on scenes, we have found relatively small year-over-year variation (smaller than 5
percent change over 10 years in the United States, in Canada an average ratio of around 0.99 for the 2011 and
2001 scene performance scores). Chapter 8 also reports on ongoing work that reverses our typical equation by
examining theories of why scenes emerge rather than focusing, as our main text does, on the consequences of
scenes.
16. Though in some cases the DDB lifestyle survey does allow us to supplement our zip code analyses with analyses
of individuals.
17. Comparing level and change is important. Levels effectively show the long-term accumulated historical residue
of years and years of residential trends; places with high levels of nonwhites or college grads are the
neighborhoods where these groups have historically lived. When change points in the same direction as level, this
suggests a continuation of the historical pattern. But when change points in the opposite direction from level (if
boomers are rising in neighborhoods where there have historically been fewer of them), this suggests a potential
shift in where this group is deciding to live.
18. Joel Kotkin (2012) reports early results from the 2010 census, which suggest the 35- to 44-year-olds of the 2000s
rose in the suburbs and declined in historic urban cores. While intriguing, this does not tell us about local-level
changes, which aggregate trends can mask. Moreover, city versus suburb tells us little about the specific types of
scenes in which any group is rising. Still, these results may suggest that the 25- to 34-year-olds of the 1990s
mellowed in the 2000s, as the boomers did in the 1990s. Our initial explorations of 2010 census data support this
general interpretation as well (see notes below).
19. Interpreting interaction terms is tricky, and chapter 8 returns to this analysis of young people, self-expression,
and transgression in more detail, investigating how spatial proximity may affect their relationship.
20. “Neo-Bohemian” amenities are defined in notes to chapter 4 and the online appendix found at
www.press.uchicago.edu/sites/scenescapes.
21. Clearly there are many overlapping processes at work here beyond an urbane “gray creative class.” Older, less
artistically active persons can be part of the “organic” feel that attracts younger, artsier people to a neighborhood;
there are “rural Bohemias” like Carmel, California, which often have many older persons; and more.
22. We consider three additional factors, after Communitarianism/Urbanity, of a principal component analysis of our
15 yellow pages–derived scenes dimensions. We add Nerdistan, the third factor of a principal component analysis
of our BIZZIP-derived scenes dimensions, because the other BIZZIP factors are either similar in composition to
our yellow pages factors or not particularly clear, while Nerdistan is distinct and points to an important type of
scene we would otherwise miss. The factor weights are detailed in chapter 8, and the analysis is based on factor
scores derived from those weights.
23. We investigated some of the determinants of LA-LA Land and the other main factors. Given LA-LA Land’s
strong emphasis on conspicuous display, a natural starting point was residential income segregation, in the mode
of claims from authors like Thorstein Veblen and Pierre Bourdieu linking conspicuousness to the perpetuation of
class distinctions. We used a measure of metro residential income segregation, taken from a leading researcher on
this topic, John Logan. Simple bivariate correlations suggest that LA-LA Land scenes (and the other factors) tend
to be in segregated metropolitan areas. However, when we adjust for only a few more variables, the connection
between segregation and scenes disappears. We performed a similar analysis of the connections between metro
income segregation and highbrow amenities, with similar results: the bivariate correlation proves to be spurious.
See chapter 8 for more details.
24. The negative association between college graduates and young people may be surprising, and indeed in a
bivariate correlation the two are positively related. The negative association in figure 5.3 appears when we adjust
for county rent. That is, holding the rent of their surrounding counties constant, there tend to be fewer young
people, the more college graduates there are. The interaction between college graduates and rent is also negative,
which suggests that as the county becomes more expensive, young people tend to be even less likely to live where
college graduate concentrations are higher. These results are examples of some of the intricacies involved in
modeling context, a theme to which we return in greater detail in chapter 8.
25. Explorations of 2010 data via regression models similar to those in figure 5.2 indicate that these general trends
persisted after 2000, as 25- to 34-year-old populations continued to concentrate in large cities, relatively nonwhite
zip codes, and arts industry clusters, as well as scenes of Urbanity, LA-LA Land, and Nerdistan. The 35- to 44year-olds of the 2000s (that is, the 25- to 34-year-olds of the 1990s) did rise most steeply in areas with smaller
youth concentrations and more white residents, as well as in more communitarian scenes. Even so, a substantial
proportion of the cohort remained in its 1990s zip codes, as there is a strong correlation (r = 0.45) between 2000
25- to 34-year-old and 2010 35- to 44-year-old population shares.
26. “Artist concentrations” are here measured as the zip code location quotient of arts jobs. This measure is similar
to the broader “cultural employment concentration” that is part of the Core, but is based on a more narrowly
“artistic” set of industries, outlined in the online appendix.
27. We include change in zip code rent in our analyses of artists because of the distinct importance of this variable in
discussions of artist-led gentrification.
28. Patterson and Silver (2015) do some related work on trends in arts organization location in Canada from 2001 to
2011, codifying and testing five hypotheses about why arts growth might grow in distinct locations, and finding a
similarly mixed and multiprocessual picture.
29. This question animates our chapter 8 discussion of the chicken-and-egg dynamics between arts jobs and total
jobs, where we show that at some time periods, arts jobs lead in sparking more total jobs; at others, the reverse is
the case.
30. If we look instead at separate dimensions and distinct amenities, we see other strong connections, which provide
further support for the general “Bronzeville and beyond” pattern. For instance, African American populations tend
to be higher in more transgressive scenes. The everyday local experiences of marginality in Bronzeville that fed
into the aesthetic and ethos of a Wright still form part of the typical day-to-day experience for many African
Americans. Moreover, we also examined links between nightclubs and African American concentrations. We
found strong positive associations, with both levels and proportionate increases in African Americans. This
finding joins Marcus Hunter’s (2010) ethnographic studies of the importance of nightclubs for urban blacks in
Chicago, which find that nightclubs are key amenities for social support, connections, resources, and pleasures.
31. Exploration of 2010 census data via similar regression models indicates that the pattern from previous decades
has largely persisted, with black population shares higher in scenes of Communitarianism, LA-LA Land, City on a
Hill, and Nerdistan, but lower in Rossini’s Tour. In the 2000s, black population shares continued to increase in
southern zip codes, those with strong cultural industry concentrations, Urbanity, and City on a Hill. The
connection between growth and LA-LA Land appears to have weakened in this period, even if LA-LA Land has
now become associated with higher levels of African American populations.
32. Parts of this section come from collaboration with Joseph Yi (Yi and Silver, 2015).
33. See Putnam (2000); and Putnam and Campbell (2010).
34. See Yi (2009) and Yi and Graziul (2011) on this topic, as well as Emerson (2006).
35. Religious studies scholar Jeffrey Kripal (2007) documents Esalen and New Ageism.
36. The history of yoga in America is a complex one, elaborated by Syman (2010). While numerous Americans
embrace (or oppose) yoga as “post-Christian,” many yoga practitioners studiously avoid any entanglement with
culture war imagery. They portray yoga as religiously neutral—neither Christian nor anti-Christian—and as
compatible with American popular culture, including its tradition of individual betterment and entrepreneurship.
This includes the first influential Hindu teacher in the United States, Swami Vivekananda, who was more
interested in raising followers and funds than in critiquing Christianity (Syman 2010, 38).
37. Our indicators of yoga and martial arts are businesses that explicitly define themselves by those labels, rather
than, for instance, as “sports and recreation facilities,” which may include both. Thus, we may be measuring more
“devotionally” framed yoga and martial arts studios and analyzing the location patterns of organizations that
define themselves in more explicit terms. Still, even among the numerous (over 60,000) and evenly distributed
(similar to New Con churches) organizations included in the “sports and recreation facilities” heading, more
include “martial arts,” “karate,” or “tae kwon do” in their names (about 900) than “yoga” (about 250). Of course
we cannot determine from these data how many general fitness businesses (such as Gold’s Gym) or city parks and
recreation centers include yoga or some martial art. It may be the case that yoga is more likely to penetrate into
less-educated and religiously conservative neighborhoods through such avenues, even as the more “devotional”
variants meet stronger cultural resistance. This would be consistent with our theorizing, but testing this
proposition is a task for future work.
38. Our definitions of conservative (i.e., evangelical) and liberal-moderate mainline Protestant follow Steensland
et al. (2000) and Putnam and Campbell (2010).
39. Yi and Silver (2015) extend the analysis to 2010, and show that these same trends largely persisted, with the
main difference being that the positive association between New Con and growth in racial diversity was
somewhat diminished.
40. Meng tests indicate that these different correlations with racial diversity are statistically different from one
another (except for the near identical correlations of Pop Culture and New Con with diversity). See Meng,
Rosenthal, and Rubin (1992). We also examined correlations of other Christian denominations with racial
diversity. Baptist, Catholic, and mainline Protestant denominations were all correlated under 0.2 with racial
diversity.
41. Clearly, many local organizations (like churches) derive numerous members/consumers from nonlocal residents
(i.e., beyond their zip codes). Omar McRoberts (2003) demonstrates, for instance, that African Americans,
especially middle-class ones, often attend churches outside the neighborhoods in which they live. This raises the
issue of catchment area, or the zone from which an organization attracts its members/customers. One relatively
straightforward way to investigate the issue is to compare county- and zip code–level variables. We did this with
our New Con index, constructing a measure of the county average number of New Con churches per zip code. In
line with McRoberts’s research, independent of New Con churches at the zip code level, African American
populations are higher and growing in counties with numerous New Con churches. At the same time, the
connection between New Con churches and African Americans at the zip code level persists, even accounting for
the county-level variable. Similarly, we find higher percentages of college graduates in counties with numerous
yoga studios, even as the strong zip code association between yoga studios and college graduates persists. We
explore further approaches to modeling spatial context in the “Modeling Context” section in chapter 8; this is an
active area of research.
42. A debate has emerged with Putnam (2007) and others writing on distrust and its strong links to neighborhood
ethnicity. They point to Mexicans and LA as extremes. Yet closer studies find dramatic differences between
Mexicans who immigrate to the United States and those who stay in Mexico. These results have implications for
other groups, but have been closely studied by Myers (2007) and Moreno (Moreno 2005, 147) who found that
while less than 10 percent of Mexicans in Mexico had “mucho” trust in the police, banks, or government, these
percentages rose to 30–40 percent among Mexicans in the United States. Myers shows continual acculturation by
Mexican Americans over time. This is quite different from popular accounts decrying “Mexifornication.”
Chapter Six
1. See Clark and Silva (2009) and Clark (2014) for these cross-national trends, as well as more specifics on key
countries globally.
2. Florida (2008) summarizes and popularizes much of the research confirming this trend; the popularity of his Rise
of the Creative Class, as well as other accounts of the change, is in part evidence for it.
3. Richard Florida and Alan Scott, for example, though writing from very different perspectives, both link regional
and city growth to the rise in culture production but leave politics out. Similarly, Edward Glaeser and Richard
Lloyd—again, very different sorts of writers—link the rise in urbanism to the growth in culture industries,
consumer cities, and postindustrial labor conditions. But they largely omit political impacts and leaders. Clark
(2004) ties variations in urban amenities to different political cultures but pays little attention to the politics and
policies of building amenities.
4. At the same time, the traditional concepts of urban political analysis—such as “regimes” or “growth machines”—
become less applicable as even Clarence Stone (2013) admits: “Has the time arrived for urban regime analysis to
receive ‘burial with honor.’ . . . The growth machine of Logan and Molotch (1987), Peterson’s developmental
politics (1981), my own work on Atlanta’s biracial coalition (1989) . . . these various analyses . . . don’t fit the
contemporary world of city politics.” New concepts, rooted in the dynamics of scenes, become more salient, as
we elaborate in more detail in Silver and Clark (2013).
5. Stinchcombe (1968, 119) observes that labor strikes were not a usurpation of an existing form of power by a new
group but rather a new way of exercising power, linked with the rise of labor markets and formally free
employment. Buzz strikes are a similarly new form of power, linked with the rise of culture. The case study of arts
activists seeking to influence condominium developments in Toronto outlined in chapter 7 (and Silver and Clark
2013) provides an illustration of how threatening a buzz strike can sometimes yield tangible results.
6. Parsons and Dahl discussed resources which Clark, J. S. Coleman, and A. L. Stinchcombe codified in exchange
matrices showing how resources could shift in prices. This chapter extends such a logic one step further by
codifying how cultural and aesthetic criteria can shift the value/prices of other distinct resources. See Clark (1973,
ch. 4); and Silver and Clark (2013).
7. chapter 7 discusses some of the broader changes Toronto has experienced within which these local issues
unfolded—political amalgamation, massive immigration, a postindustrial creative economy, and a “cultural
renaissance”—as well as another case in which the interplay between scenes and local economic development
became highly politicized, releasing somewhat different dynamics than in the Wychwood Barns case. Grodach
and Silver (2012) document nearly 20 case studies of similarly contentious politics around urban cultural policy.
8. Our analysis of the area shows that from 2001 to 2006, the percentage of residents in the postal code reporting
“multiple ethnic origins” (to Statistics Canada) went from 34 percent to 43 percent, compared to a citywide
average in 2006 of 30 percent. The percent of “multiples” was highest in the census tract beside the Barns.
Around nine percent of the ward’s population work in arts, culture, and recreation, and 16 percent work in social
science, government, and education—both well above the city average. About 35 percent of residents have
degrees in humanities or social sciences, while by contrast about 12 percent have degrees in engineering or the
technical trades. At the same time, fewer people work in manufacturing than in the average Toronto neighborhood
while more work at home and walk to work.
9. Blow-by-blow details of how this occurred are in Berland and Hanke (2002) and Lorinc (2002).
10. See Klandermans and Tarrow (1988).
11. This shift from production and hierarchy to consumption as models of political behavior was one of the main
themes in Personal Influence (Katz and Lazarsfelds 1955). Not only does this shift change the way we look at
politics by focusing attention on local opinion leaders and informal conversations; it also potentially reverses the
standard causal direction, in that consumption and taste patterns may influence political decisions. Lipovetsky
(1994) extended these ideas, suggesting that the pluralism of fashion prepares citizens for the pluralism necessary
for a functioning democratic polity.
12. See Ramirez, Navarro, and Clark (2008).
13. This sensitivity is explored by Kevin McDonald (2006).
14. See Clark and Hoffmann-Martinot (1998).
15. Urbanity is a factor summarizing the 15 scenes dimensions. It stands out here in that for the most part the same
variables that account for where there were any NSMs typically account for where there were more. There were
some exceptions. In particular, Democratic voting was not related to the presence of any NSMs but was positively
related to whether more NSMs were present. By contrast, county crime rates were slightly positively related to
NSM presence but not related to whether there were more NSMs. Similarly, county population was related to the
presence of NSMs but was not related to their number (there were fewer of them where the population was higher,
even if there were usually some). Moreover, areas experiencing increases in neighborhood rent were less likely to
have any NSMs, but given at least one NSM, rent increases had no relationship to whether there were more or
fewer NSMs. It may be that increasing rents indicate gentrification, and an additional cost burden for founding
NSMs, while Democratic voters are more likely to engage in NSMs. Conversely, higher crime rates may create a
demand for human rights and social advocacy organizations, but high crime areas have less resources to support
multiple NSMs. The role of population size is less clear.
16. While these activist NSM organizations are not significantly associated with transgressive zip code–level scenes,
we find that counties with more transgressive scenes on average across their zip codes do tend to be more
politically liberal (in the sense of typically voting for Democratic presidential candidates). The political meaning
of “transgression” is variable and complex.
17. We find a similarly strong effect on NSMs from the interaction between walking and glamour, even accounting
for the interaction between walking and self-expression. Teasing out these sorts of subtle relationships between
walking, other aspects of urban form, the arts, scenes, and politics is a research area we are actively pursuing with
Brian Knudsen, some of which appears in Knudsen and Clark (2013) and Knudsen, Clark, and Silver (2016).
18. This general concern with the actions of ordinary citizens led political theorizing to connect everyday decisions
to the political process. A case in point is migration. The Tiebout hypothesis (from economist and geographer
Charles Tiebout) holds that people vote with their feet and choose a place to live in conjunction with
considerations about public services provided by local governments. Moving from one town to another is thus a
political statement that reveals the sort of community in which one would like to live. The analyst is accordingly
impelled to understand what sorts of political communities and institutions attract what sorts of persons, and vice
versa. Economist Albert Hirschman similarly framed residential choices as a political decision between exit,
voice, or loyalty: you can remain true to your community through thick and thin (loyalty), agitate to change things
(voice), or leave town (exit). Whatever the decision, however, the analytical framework stresses that these are
citizen choices, and that local governments compete with one another to retain residents’ loyalty, and with it, their
votes. In this way localities come to reflect divergent political orientations.
19. Updating the Lazarsfeld-Lipset-Rokkan contextualist line of thought, recent politics research includes Gelman
(2008), who showed how individuals’ voting behavior varied with the income of their states, and Bartels (2008),
who similarly showed that affluent persons differ politically in red and blue states. There is also a strong tradition
of contextual analysis in political geography, especially in the United Kingdom and France, with Ron Johnston’s
work as a leading example (e.g., Johnston 1983, 1987). In the United States, James Gimpel and his collaborators
have detailed how local context shifts political outcomes from turnout to voting to financial contributions (e.g.,
Gimpel, Dyck, and Shaw 2004; Gimpel, Kaufmann, and Pearson-Merkowitz 2007; Gimpel, Lee, and Kaminski
2006; Gimpel and Schuknecht 2004).
20. Figure 6.6 shows results for our yellow pages dimensions, but scenes constructed from BIZZIP data show much
the same pattern. These shifts relate to education, religiosity, and voting trends, noted below.
21. The same survey found that 73 percent of consistent liberals and 23 percent of consistent conservatives said
being near art museums and theaters is important in deciding where to live. See Pew Research Center, “Political
Polarization in the American Public: Section 3. Political Polarization and Personal Life,” June 12, 2014, accessed
June 5, 2015, http://www.people-press.org/2014/06/12/section-3-political-polarization-and-personal-life/.
22. Why this alignment is occurring is not so clear. Bishop’s (2008) The Big Sort pointed toward migration and
residential sorting: less constrained by extended family obligations and more educated and mobile, individuals are
more and more moving to culturally congenial cities. Morris Fiorina, by contrast, maintains that “conversion” not
migration is the key driver. People increasingly want their party allegiances to align with their ideological and
cultural values. Accordingly, “conversion” to issue positions consistent with one’s party produces a stronger
alignment between cultural outlook and political allegiance.
23. These religion data come from the Religious Congregation and Membership Study’s US Religion Census.
“Adherents” are estimates by the minister of the number of persons attending an average weekly service, “the
most complete count of people affiliated with a congregation, and the most comparable count of people across all
participating groups. Adherents may include all those with an affiliation to a congregation (children, members,
and attendees who are not members)” (Association of Statisticians of American Religious Bodies 2010).
Evangelical Protestants here include 146 denominations, which “emphasize a personal relationship with Christ,
the inspiration of the Bible, and the importance of sharing faith with non-believers, Evangelical Protestantism is
usually seen as more theologically and socially conservative than Mainline Protestantism” (Association of
Religion Data Archives 2010). For all variables used in analyses of 2008 and 2012, we used 2010 data where
possible.
24. While other ways of measuring union strength are of course possible, nationally well-known union towns like
Milwaukee and Cuyahoga Counties rank high on this measure; unions’ strong associations with Democratic
voting and turnout add further face validity.
25. Turnout is defined as the total county votes per capita for each election year.
26. Brint and Schroedel (2009) pursue many of these themes in more detail.
27. The corresponding rightward shift of Catholic areas also illustrates one of Putnam and Campbell’s points:
namely, that in the present period, denominational differences in politics are receding and a more general politics
of “religious versus nonreligious” may be emerging. Further analyses we performed suggest some important
qualifications to this statement, however. Using geographically weighted regressions, we found that the Catholic
shift right was strongest in the South and barely present in the West, where Catholic areas continue to be reliably
more Democratic. National averages can miss these geographic differences, which suggests paying attention to
how distinct local processes may be driving these trends.
28. See J. Johnston and Baumann (2007).
29. If we analyze individual behavior and attitudes in the DDB survey, we find similarly striking patterns. Highincome individuals tend to identify as Republicans. Yet wealthy individuals who also give more “egalitarian” and
“self-expressive” survey responses are more likely to identify as Democrats. Income is not political destiny.
(Examples of “egalitarian” responses are as follows: supporting women’s liberation and gender equality in the
workplace; supporting unions, recycling, or community projects; and wanting to learn from other cultures.
Examples of “self-expressive” responses include attending cultural events like concerts and museums, wanting to
look different from others, not wanting to be stuck in routines, relishing cultural change, and the like.)
30. This section draws on collaboration with Diana Miller, who led in Canadian research on scenes and politics.
31. In this regard scenes analysis builds on past work on contextual effects and local area processes, such as Elazar
(noted above), Lipset (1990), Stewart (1994), Wiseman (2007), and others. Johnston (1983), for example, finds
that the strength of partisan opinion in local context shapes individuals’ political sensibilities, and can either
counteract or exaggerate national political trends. Cochrane and Perrella (2012) similarly find that individuals’
political preferences are shaped not only by their personal economic situations but also by the economic situations
in their local constituencies. Individuals’ spatial context also shapes their social networks, which in turn shape the
kinds of political information they receive (Bramlett, Gimpel, and Lee 2011; Huckfeldt and Sprague 1987;
Zuckerman 2005).
32. Sampson (2012) reviews these levels of explanation and others, including individual to collective (i.e., how
individual behavior generates aggregate patterns), individual to individual (i.e., how individual behaviors
influence other individual behaviors), and “bird’s-eye” processes that link neighborhoods to one another and to
the broader world around them.
33. We did explore the DDB in the United States and found that results for individuals are largely consistent with the
aggregate patterns we report in this chapter. For instance, individuals who live in more neighborly and traditional
scenes show less support for socially liberal ideas (accounting for their age, sex, race, education, and income),
while people who live in Bobo scenes (as defined above) show more. While intriguing, these initial findings and
data sources have their own limits, and so we only flag them here as pointing in an important direction of ongoing
research.
34. Conducted by IPSOS, a private polling firm, this poll is an Internet-based opt-in survey of 39,236 Canadians,
selected from a standing panel of over 200,000 members, who are nested within 307 electoral districts (EDs).We
exclude one electoral district, Malpeque, from our analysis due to data limitations that prevented us from
obtaining an accurate count of the amenities there.
35. There are certainly drawbacks to using Internet opt-in surveys (cf. Chang and Krosnick 2009). However, we
have taken precautions to minimize those drawbacks, elaborated in the online appendix
(www.press.uchicago.edu/sites/scenescapes).
36. These data have barely been examined by political scientists and geographers. James Gimpel has been a leader.
With collaborators Frances Lee and Joshua Kaminski, he found that surrounding context strongly influenced
contributions. Zip codes gave more when they were near other zip codes that were also high contributors; this
contextual effect, they found, was not simply a reflection of higher income. Another study (Bramlett, Gimpel, and
Lee 2011) of attitudes of individuals in the country’s highest-contributing zip codes (whether Republican or
Democratic) found that big-donor areas were more socially liberal.
37. See especially Beisel (1997); Khan (2010); Kendall (2008); and Mayo (1998).
38. See Karabel (2005).
39. Here is just one example of the sorts of combinations we explored, often adding one or two scenes measures to
classic voting models. Specifically, the interaction of our Rossini’s Tour factor score (discussed in chapter 5) and
Blue Blood amenities is negatively and significantly associated with Republican voting. Nantucket,
Massachusetts, illustrates the process. Nantucket County ranks 394th nationally on the Blue Blood index but rises
to number 50 on the Rossini’s Tour–Blue Blood interaction. Nantucket voted for Republican candidates in all but
one presidential election from 1960 to 1984 but has since overwhelmingly voted Democratic. Income is used in
two ways in political and economic studies. The first is to impute interests or tastes to persons, based on their
income: “rich people like X.” The second is to use income as a resource, which stresses that it is limited but can
be exchanged. Yet it does not index preferences, or it does so poorly. We prefer this second usage, which makes
more explicit the necessity to add preferences from some other source. This is a core issue to which scenes bring
value: examples in this chapter are often drawn from related lifestyle indicators, from the transgression of Bobos
to the club memberships of Blue Bloods.
40. We performed numerous analyses to assess the robustness of the link between Blue Blood amenities and partisan
contributions. For instance, we analyzed the Blue Blood share of total amenities rather than the count of total Blue
Blood amenities to check for size effects. Other analyses of total Blue Blood amenities controlled for total
amenities, zip code total population, population density, and various measures of wealth such as per capita
income, median rent, and median household income. We consistently found a strong association between Blue
Blood amenities and partisan contributions.
Chapter Seven
1. These results held in many countries including the United States and Canada. See Clark (2014).
2. Similarly, Americans for the Arts reports big increases in smaller nonprofits and the beginnings of a post-2007
recession rebound in arts participation; similar data on dynamic but undercounted small and informal groups and
activities have been presented by Jennifer Novak at Wolf Brown, among others (Kushner and Cohen 2013;
Greater Philadelphia Cultural Alliance 2009).
3. Major public policy support for the arts is old in Germany for opera and France for theater, festivals, and more,
but many of their official cultural policies are more recent, as are incipient moves toward increased attention to
smaller, less formal, and less established arts groups and activities. For several case studies about emergent trends
in European cultural policy, see Grodach and Silver (2012).
4. For more on Asian immigrants in Flushing, New York, see Jefferson Mao’s interesting discussion here: “On
Gentrification in an Unhip Place,” Next City, March 25, 2013, accessed June 8, 2015,
http://nextcity.org/daily/entry/letter-from-flushing-on-gentrification-in-an-unhip-place.
5. There are also difficulties in evaluating whether displacement is occurring, and whether gentrification is its cause,
as well as challenges in assessing the various sorts of harms and benefits involved. Even assessing the scope of
gentrification is difficult, as it may be a much more rare phenomenon than its media presence would suggest. See
Vigdor (2002); McKinnish, Walsh, and White (2010); Sheppard (2012); Sharkey (2013); Hwang and Sampson
(2014); Freeman and Braconi (2004); among others.
6. Kimelberg and Williams (2013) review recent research on business location factors and report on their survey of
real estate professionals, which found that quality of life concerns tend to be more important for offices than for
manufacturing or retail.
7. See Nicodemus (2013).
8. These figures are based on our Canadian yellow pages amenities database.
Chapter Eight
1. Other metaphors are certainly possible, such as comparing scenes to recent work in psychology on the big five
personality traits and their spatial distribution within and across communities. We have sharpened several
measurement concerns through building on work by James Heckman (2011), who has critiqued the
methodological work on the big five.
2. Sampson, Morenoff, and Gannon-Rowley (2002) reviews many of these methods, while Logan (2012) discusses
the current state of the art in spatial analysis. Anselin (1988) pioneered the field.
3. See Alexander (2003) and Borer (2006).
4. As in Parsons (1951) and Swidler (1986), respectively.
5. Cf. Gieryn (2000)
6. Cf. Duneier (1999); Borer (2008); Grazian (2003); Suttles (1984); and Latour, et al. (2012).
7. See Mohr (2003) and Yeung (2005). See also Abbott and Hrycak (1990); among others.
8. See Irwin (1977); Blum (2003); Straw (2001); and Hitzler (2005).
9. See http://faui.uchicago.edu.
10. Simpson and Judd (2011) present a debate among participants from several theoretical perspectives.
11. See Jang, Clark, and Byun (2011); and Clark (2014).
12. See Zelenev (2004).
13. Atomism is not unique to economists. Many journalists, popular commentators, and social scientists have
utilized the presence of a single amenity (e.g., Starbucks, craft beer, etc.) to impute local cultural trends. John Levi
Martin (2011) provides a conceptually subtle discussion of holism and fields and how they can transform
theorizing generally.
14. Renewed interest in “activity spaces” by social scientists suggests that data on those who frequent these
amenities may also become available in the near future, though unless proprietors provide their own data this is
unlikely to satisfy our need for geographic comprehensiveness. See, for example, Mennis and Mason (2011).
There are many related developments involving social media and other Internet products, plus big data from
multiple new sources.
15. See Van Deth (1998); and Kaple, Rivkin-Fisch, and DiMaggio (1996).
16. Information regarding the location, industry, and number of employees is largely derived from the Employer
Identification Numbers (EINs) assigned by the Internal Revenue Service. Where multiple establishments share the
same EIN, a unique employer unit identification number exists. Where reporting of information would identify
firms, data are censored.
17. Cf. Zelenev (2004).
18. Tim Hotze led in developing protocols for downloading yellow pages data and in checking for errors, duplicates,
consistency, coverage, and completeness. For Canada we used yellowpages.ca.
19. See Rothfield, Lee, and Silver (2007); Brydges et al. (2013); and Lee and Silver (2014).
20. See Hyman, Levine, and Wright (1967) for an early example of the use of expert informant surveys for crossnational comparative research. Evans and Rauch (1999) and Rauch and Evans (2000) represent more recent work
using a similar paradigm.
21. Besides these five scores, two more were coded. The first, 88, indicates that coders did not feel that they
understood an amenity well enough to make a determination. Giving coders a way of saying “I don’t know”
improves the reliability of the analysis by reducing the number of speculative scores. The second score, 99,
indicates an inadequate level of specificity in the amenity category. Using 88 and 99, while not directly
incorporated in most analysis, in early rounds of coding gave us indications of what additional sources of data we
should look for.
22. With so many data points and indicators, however, specific decisions often make a relatively trivial contribution
to the overall scores, as we illustrate in the online appendix.
23. Cf. Verba, King, Keohane (1994).
24. While data sets with a large number of cases can tend to inflate the significance of exceedingly modest
relationships, our hypotheses typically state directional relations (+ or −), which we interpret one by one. Many
are disconfirmed. The relative size of the effects involving scene variables often rivals other classically used
variables (e.g., education as one of our Core items).
25. While we do not report intensity scores in this volume, we consider them more than just an intermediate step
toward performance scores. In particular, they help discern which amenities are major drivers of particular
subdimensions (i.e., we can tell the difference between an overwhelming number of slightly traditional amenities
versus a small number of extremely traditional amenities).
26. For instance, we also computed performance scores based not on organizational counts but on employment
counts, which helps adjust for the size of an organization. This approach gives added weight to a single museum
with many employees over several small museums.
27. Another combination that we explored is the cultural diversity index (CDI). The CDI is a way to measure
whether a place’s overall scene profile is diverse or focused. Take, for example, Times Square in New York,
where walking along a single block, one might encounter hippies and yuppies, preachers and agnostics, selfexpression at one turn and corporatism at another. The CDI measures the extent to which amenities within a zip
code are divergent or similar. Mathematically, the CDI score for a zip code was the average of all the coefficients
of variation from each of its 15 dimensions. We found it positively related to crime rates, when controlling for
other standard items, for instance.
28. We explored the internal consistency of these additive indexes using Cronbach’s alpha, which is the statistic
typically used by psychologists to evaluate the reliability of scales that add multiple indicators. There is some
debate as to how to interpret a “good” alpha. Some suggest aiming for a range from 0.6 to 0.9 depending on the
purpose of the scale and the nature of the data. Given that our N is much higher than the typical psychological
study (usually below 100), we were comfortable with alphas at the lower end of the spectrum. In this light the
alphas for the New Con and Neo-Bohemian indexes look quite strong (over 0.8); and the alphas for the Blue
Blood, Mainline Church, and Pop Culture indexes look adequate to moderately strong (between 0.6 and 0.7). The
alpha for the New Age index is lower, probably due to the low number of items in the index (only 3) and the large
disparity in the Ns of its components (there are far more yoga studios than metaphysical bookstores and
meditation centers). This of course implies that the New Age index results are largely driven by yoga studios,
which we confirmed by running those analyses with yoga alone and finding minimal differences from the index.
Making yoga a centerpiece for measuring the “holistic milieu” is consistent with the work of leading researchers
on the topic like Paul Heelas and collaborators.
29. The Core includes both zip code– and county-level variables, as detailed in the online appendix and noted in
captions to tables and figures. The main reason for including county-level variables is substantive: we are
interested in, for example, whether being in a big county with a high cost of living may account for the processes
we are observing. Other variables, such as the normalized FBI crime rate data, are only available at the county
level.
30. Some summary descriptive statistics for our performance scores are in the online appendix, as well as in chapter
3.
31. This pattern is documented in Elazar and Kincaid (2000). Sampson (2012) similarly shows that over nearly a
century the relative differences among Chicago neighborhoods on a host of dimensions barely changed.
32. For our performance scores, however, we imputed values of 2.99 to zip codes for which we could not compute
an actual score The value of 2.99 was chosen instead of 3.00 (the score indicating a null scene) so that we could
differentiate the imputed values from the weights assigned to coders should we choose to analyze them separately.
33. Results reported in Scenescapes therefore are from analyses that delete missing cases in listwise manner—
deleting all cases from a model if they are missing on any variable in that model—since mixed/multilevel models
require this method of handling missing data.
34. To make these graphics, we used R’s visreg package and Stata’s marginsplot command.
35. This was accomplished by exporting a spreadsheet from ArcGIS 10 that listed target zip codes in one column
and neighboring zip codes in another. If a zip code had five neighbors, there would be five rows of identical
entries repeated for that zip code adjacent to five different values of each of the neighboring zip codes. It was then
a simple procedure to merge our target zip code with the average score for its neighbors (all adjacent zip codes)
using SPSS, calculate the average value for these neighbors via the AGGREGATE command, and add the
resulting average neighbor’s score to our scenes database. The method is illustrated in the below examples with
percent nonwhite and performance measures.
36. Our use of adjacency to parameterize spatial relationships is uncommon in the sense that decades of researchers
have explored nuanced ways of accounting for spatial relations. This typically involves weighting the importance
of nearby locations according to distance in a way that accounts for nonadjacent geographies. Such an expanded
view of spatial dependence may be sensible for commuting to work or shopping; for culturally sensitive scene
aficionados, the effect of the nearest locations may be more important. We report sensitivity tests below for
differing degrees of proximity.
37. It is worth noting that measures which combined multiple scenes dimensions, such as our Urbanity measure, do
so within a zip code. We did not explore the generalization involving multiple zip codes, largely given the
technical issues involved and the fact that our bivariate correlations involving neighboring zip codes were so
weak.
38. This approach differs from a standard one that flags significant spatial autocorrelation as indicated, for instance,
by Moran’s I and stops there, with the flag labeling a “problem.” Looking at how effects shift depending on
combinations of several variables in space is closer to the logic of geographically weighted regression (GWR),
noted below.
39. These effects are in addition to rent prices, which are included at the county level in results reported in the text.
Adding zip code rent to the model does not alter the scenes results. We also examined average rents of
neighboring zip codes and found no significant relationship between nearby rent and change in 25- to 34-year-old
population; nor did we find any significant interaction between self-expression and adjacent rent.
40. HLM 7 was used to estimate our models here. Similar results are produced by Stata’s xtreg, SPSS’s mixed, and
R’s lmer commands, which were used for most multilevel analyses reported in chapters 4, 5, and 6.
41. We also examined a multilevel model with the transgression performance score as a random effect, which did
not appreciably alter the fixed-effects results. The model fit statistics in table 8.8 suggest that the standard
modeling approach to geographic context (i.e., cross-level interaction) does not perform better than using scenes
data from adjacent zip codes. In fact, the standard approach may miss the significant independent effect of having
transgressive neighbors, regardless of a location’s self-expression. Overall this suggests that the mechanism
behind scenes’ effects may in this case operate at a geographic scale smaller than the county.
42. Here is the St. Louis Riverfront Times: “The most impressive work of art is the village itself, a warren of narrow
lanes and nineteenth-century storefronts surrounded by green hills. Visitors approach the pocket-size town on an
arched stone bridge so weathered you’ll expect to find trolls living underneath it. Maeystown’s natural and manmade vistas go beyond mere ‘quaint’ or ‘picturesque’ into the realm of the truly beautiful” (quoted on the
Maeystown website, accessed June 9, 2015, http://www.maeystown.com/).
43. Selective examination of the geographies produced by this approach suggests that R = 3 catchment areas can
effectively mimic counties (in terms of square miles and population).
44. Geographically weighted regression (GWR) represents another approach to the multivariate analysis of spatial
data that takes into account the local values of the variables being employed. We have run dozens of GWRs using
scenes data as did Wu (2013). Attractions are its ability to manually or analytically specify bandwidths and
estimate shifting regression weights from closer versus more distant geographies. Despite some limitations, GWR
is a key ongoing area of research and a prime candidate for investigating in more detail how scenes dynamics vary
in different contexts. The maps are descriptively attractive but harder to interpret than the specific results reported
here.
45. See Alexander (2003).
46. Giddens (1984) provides a major theoretical statement about the issue of “recursivity.”
47. It was actively debated for several months in exactly these terms on the ComUrban electronic mailing list, by
some 800 urban members of the American Sociological Association, excerpted in Clark (2004, ch. 11).
48. For an update, see Gebremariam et al. (2007).
49. Cristina Sakamoto worked on chicken-and-egg analyses with us for several years. This section illustrates some
clear and important results. She has reported more in papers to the International Sociological Association and
American Sociological Association.
50. Specifically, to examine the more Bourdieusian claim, we made highbrow and lowbrow indexes and treated
these as outcome variables. The general picture is similar to what we report in the text for the performance score
factor scores: there is a positive bivariate relationship between metro income segregation and highbrow amenities,
but that connection becomes statistically insignificant when we add only a few more variables.
51. Reardon and Bischoff (2011, 9–10) describe “H” as follows: “This measure compares the variation in family
incomes within census tracts to the variation in family incomes in the metropolitan area. It can range from a
theoretical minimum of 0 (no segregation) to a theoretical maximum of 1 (total segregation). In a hypothetical
metropolitan area in which the income distribution among families within every census tract was identical (and
therefore identical to the overall metro income distribution), the index would equal 0, indicating no segregation by
income. In such a metropolitan area, a family’s income would have no correlation with the average income of its
neighbors. In contrast, in a hypothetical metropolitan area in which each tract contained families of only a single
income level, the index would equal 1. In such a metropolitan area, segregation would be at its absolute
maximum; no family would have a neighbor with a different income than its own. Although the magnitude of H
does not have a particularly intuitive meaning, differences in H between metropolitan areas or changes over time
indicate where and when segregation is higher or lower.”
52. This is the approach followed by recent studies of segregation by race and income in the United States and
Europe. But we note that the geographic segregation focus assumes at least moderate residential mobility and a
search for location among persons similar in consumption practices—which holds less in the past and in more
traditional societies. In the American South, for instance, it was once said that “in the South it doesn’t matter how
close Negroes get as long as they don’t get too high; in the North, it doesn’t matter how high they get as long as
they don’t get too close” (Egerton 1995, 50, quoted in Lloyd 2012). But since the United States and some other
societies are moving toward this northern model, we follow it here as well.
53. Cf. Boschma and Fritsch (2009).
54. For example, the urbane side of the Canadian factor focuses more exclusively on formality, corporateness, and
utilitarianism, whereas the US version includes these together with glamour and transgression.
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Index
The letter b following a page number denotes a box; the letter f, a figure; and the letter t, a table.
activists, 232, 398n16
adjacency, analysis of, 350, 355, 356, 405–6n36
aesthetics: baby boomer migration and, 188; configuration of meanings, 31; human rights and, 247; molecular level
of, 20–22; new social movements and, 242–54; performance, 98; scene recognition and, 5; view of place, 1–2. See
also specific dimensions
affordances, judgements and, 5
African American neighborhoods: Bronzeville, 192–95; characteristics of, 285; local amenities in, 13; location
choices, 193f; New Con amenities in, 215; nightclubs and, 394n30; studies of, 391n11; urban revitalization and,
354
age groups: healthy aging, 296–97b; scene choices and, 180–82. See also ruppies; young people
Almond, Gabriel, 254
amenities: coding of, 332–34, 336f; cultural patterns revealed through, 76–95; definition of, 33b; dimensions and
coding of, 333–34; locations of, 69; nationwide database of, 323; political ideologies and, 258; by region, 84–85t;
scenes and, 95–103; subnational cultural differences, 83; theorizing by economists, 325–26; variation in meaning
of, 381; weighting of, 98–99, 110–11t
Anderson, Chad, 68, 380
Andersonville, Chicago, 47
Arendt, Hannah, 268
Arieff, Allison, 306–7b
Arrigo, Vincent, 68, 391n8
Arrow, Kenneth, 256
art: dealers, profile of, 338t; gallery distribution, 83–86; grants, 295; management professionals, 235. See also
artists; arts amenities
artistic dividends, 138, 148–50, 149f
artists: communities of, 221, 222f; concentration of, 188–92, 393n26; economic growth and, 313–14; emotional
engagement and, 233; heterogeneity of, 189; high crime areas and, 155; independent, 93; learning from, 245b;
local contributions of, 235; scene creation by, 288b
ArtPlace America, 297–98
art professionals, 389n13
arts amenities: citizen’s interest in, 231; concentrations of, 190f; distribution of, 83; employment related to, 12f,
189–90; growth of, 11; impact of, 150; jobs related to, 372–75, 375f
Artscape Wychwood Barns, Toronto, 241
atomism, 325–26, 403n13
attention, styles of, 268
authenticity: amenity indicators, 100–101t; analytical components of, 41, 41t; analytical dimensions of, 42t; coding
questions, 337t; descriptions of, 37–38; dimensions of, 46–52; enhancement of, 157–59; ethnic, 386n6; local,
140–41; local development and, 232; married couples and, 391n13; Ngram of, 38f; political culture and, 234;
population growth and, 159; self-expression and, 185; walkable places and, 158b, 289
baby boomers: consumerism by, 180; great aesthetic migration and, 188; location choices by, 181f, 186f; population
trends, 182; retirement of, 14b; scene choices and, 180–82; sensitivity to scenes of, 284–85
Bachelard, Gaston, 102b
Becker, Gary, 11
Bell, Daniel, 11–12, 49, 53b, 54, 172
Bellah, Robert, 54, 77
Bellow, Saul, 8b, 49
Bender, Courtney, 206b
Berkeley, California, 99, 102
Berman, Marshall, 51b
Bishop, Bill, 13, 196, 220
BIZZIP (Zip Code Business Patterns), 72–76; amenities, nationally, 78t; amenity counts using, 76, 77; data from,
328–32; descriptive statistics from, 331f; face validity of, 95; performance scores and, 358–59t
Black Is Beautiful, 66b
Blair, Tony, 270
Blue Blood amenities, 273, 401n39, 401n40
Blue Blood index, 224, 275, 277f
Blum, Alan, 44
“Bobo” effect, 27; political culture and, 263–65
“Bobo” index, 264–65, 266f
Bobos: in Bridgeport, Chicago, 291; formula for, 63b; patterns, 274
Bohemias: added value, 157; aesthetic, 59; “bliss point” in, 342; county communitarian-urbanity scores, 156f;
economic impacts of, 155; ideal-typical scene dimensions, 63t; political action and, 250b; rural, 392n21;
surroundings of, 139–42. See also “Bobo” effect
Boltanski, Luc, 171
Bourdieu, Pierre, 33b, 376, 385n1 (ch. 2), 393n23
Brainard, Jim, 142, 159, 287
Brecht, Bertolt, 65b
Bronzeville neighborhood, Chicago, 19, 394n29; characteristics of, 285; cultural dimensions of, 192–95; historical
context of, 66b; Soulman statue, 162
Brooks, David, 27, 224, 263, 264b, 290–91
Brooks, Peter, 63b, 65b
Brown, Judith, 43
Brown-Saracino, Japonica, 43–44, 47
Bush, George W., 18, 223, 262
“buzz”: description of, 223, 231; geography of, 43; inflation of, 233–34; local politics and, 223–24; political
contexts of, 237t; political engagement and, 232; sustainability of, 234; value of, 231–32
Calvinism: “good soil” metaphor, 133; predestination in, 131–32
Carmel, Indiana, 142, 287
Castells, Manuel, 172
catchment areas, 364–67
Catholicism: Chicago and, 93, 118–19; political ideology and, 261; tradition in, 52
causality, problem of, 369–72
charisma: dimensions correlated with, 116–17, 117f; legitimacy and, 52, 101t
Chiapello, Eve, 171
Chicago, Illinois: amenity value of, 13; Andersonville, 47; Argyle Street, 47; Bohemian scenes, 380; Bridgeport,
170b, 171, 291; Bucktown, 363–64; charisma, 117, 117f, 118–19; cultural crucible of, 115–19; cultural identity of,
169–70; economy of, 95b; ethnic bases of, 385–86n3; ethnic neighborhoods, 32; expressive revolution in, 8b; fast
food amenities, 91; Gold Coast, 363–64; Irish Catholic dominance, 167b, 385–86n3; languages in, 169b; local
pubs in, 107b; Loop area, 32; neighborhood sculpture in, 5; neighborliness of, 107b, 113f; New Chicago School,
165–76; Pilsen, 139; political organizations, 386n4; politics, 171; precinct captains, 172; scenes from, 105–6; selfexpression, 113f; sensitivity to “outsiders,” 170b; top amenities, 88–90t; traditional ethos of, 93, 95; walking pace
in, 71; Wicker Park, 15, 32, 191; Wrigleyville, 99, 102–3. See also Bronzeville neighborhood, Chicago; and
specific neighborhoods
chicken-and-egg dynamics, 370–75, 394n29
churches: dimension features of, 115; distribution of, 83–86; ethnic neighborhoods and, 166–68; location choices
and, 198; locations of, 385n2; New Age, 203; parishes, 166; racially segregated, 198; residential choices and, 166;
by zip code, 213. See also specific churches and religions
cities: ambition and, 87b; building scenes for, 303–5; classical conflicts in, 225–27; consumption by, 12–13; cultural
differences, 86–95; gentrification of, 291; global factors in politics of, 230f; livability measures, 292; migration
patterns, 290–91; political agendas of, 225–27; resistance to tradition by, 109–14; walkability of, 252b. See also
specific cities
City on a Hill: African American populations and, 394n31; artists and, 189; baby boomers and, 185; income
inequality and, 377; scene dimensions, 183
Clinton, Bill, 18, 223, 243, 270
Coleman, J. S., 396–97n6
Communitarianism: African American populations and, 394n31; African Americans and, 194–95; American scenes
and, 115; Bohemian islands in, 155–57; rents and, 190–91; Republican counties and, 224; urbanity versus, 115
Communitarianism/Urbanity scores, 342–43; income inequality and, 377; measures, 179; Nerdistan and, 392–93n22
consumption: by cities, 12–13; laboratories of, 14; leisure and, 11
contextual effects: local processes and, 400n31; spatial differences and, 268
Converse, Philip, 254
Core. See “the Core”
corporate amenities: authenticity and, 100t; distribution of, 83
corporateness, 48–49
creative classes: artist communities and, 150; Canadian definition of, 389n13; “gray,” 392n21; income and, 378–79;
in Spain, 172, 378–79
culture: city politics and, 230f; household spending on, 228; local, 30–31; sociology of, 375; values and, 30
Currid, Elizabeth, 14–15, 43, 92, 136b
Dahl, Robert, 273
Daley, Maggie, 282
Daley, Richard J. (Mayor Daley I), 5; changes to Chicago, 114; parochialism of, 118b; urban policy under, 282
Daley, Richard M. (Mayor Daley II), 171, 243; urban policy under, 282
DDB lifestyle survey, 74
Dewey, John, 6b
DiMaggio, Paul, 273
dimensions: combinations of, 342; ideal-typical Bohemian scenes, 63t; as leitmotifs, 59–66; scene decomposition,
56
Disney Heaven scene, 61b, 67f
Downs, Anthony, 256
Driscoll, Mark, 207
economic development: artistic amenities and, 148; Bohemia and, 156f; glamour and, 151–54; measurement of,
143–44; performance scores and, 151f; Renoir’s Loge and, 149f, 150; scenes and, 121–61; self-expression and,
145f, 151–54; technology clusters and, 145f
education: arts jobs and, 374–75, 375f; effects of, 267; lifestyle characteristics, 390n18; politics and, 270–72; scenic
influence on, 271f. See also university graduates
egalitarianism: charisma correlation with, 117–18, 117f; legitimacy and, 54, 101t; social movements and, 235; town
meetings and, 257; voters and, 236
Eisenstadt, Schmuel, 256
Elazar, Daniel, 257
Emanuel, Rahm, 288b
Emerson, Michael, 200, 201b
Emerson, Ralph Waldo, 54
empowerment: of citizens, 294; success and, 316
Eno, Brian, 137b
Esalen Institute, California, 202–3
ethnicity: authenticity and, 47, 100t; distrust and, 395–96n42; life choices and, 196
evangelical churches: appeal of, 219; location choices and, 198
evangelicalism, politicization of, 262
exhibitionism, 45–46, 100t
Falck, Oliver, 171
Fiorina, Morris, 399n22
Fiscal Austerity and Urban Innovation project, 287b, 323
Fischer, Claude, 196
flâneur, description of, 70–72
Florida, Richard, 396n2, 396n3; on amenity-driven migration, 173; on artists and economic development, 150; on
attraction for young people, 180; on the creative class, 229; critique of Friedman, 83; on location selection, 371;
Martin Property Institute and, 311; notion of Bohemia and, 60, 63b, 138
Fogel, Robert, 11, 199, 262–63
formality: political ideologies and, 258; theatricality and, 45, 100t
Friedman, Thomas, 83, 130b
Fritsch, Michael, 171
From the Ground Up (Stolarick et al.), 310, 315
FSAs (Forward Sortation Areas), 74, 108, 148
Gardiner, Fred, 245
Gates, Theaster, 286, 288b
Gemeinschaft: Gesellschaft versus, 143; typical American scenes and, 115
Gemeinschaft-Gesellschaft complex, 115–19, 116b, 380
gentrification: African American, 194–95b; artists and, 191–92; of cities, 291–92; displacement and, 402n5;
resistance to, 192; story of, 189
Gesellschaft: Gemeinschaft versus, 143; typical American scenes and, 115
Gimpel, James, 398n19
Glaeser, Edward, 11, 12, 95b, 142, 173, 229, 371, 396n3
glamour: charisma correlation with, 117f; definition of, 44b; economic growth and, 151f; grit as, 45b; growth
impacts, 389n14; local development and, 232; self-expression and, 151–54; theatricality and, 43, 100t
globalization: aesthetic criteria and, 65b; social-psychological effects of, 282; urban policy and, 281–82
Goffman, Erving, 38, 45, 65b
Gore, Al, 273
Graham, Paul, 87b, 91
Graña, César and Marigay, 64
Grazian, David, 47
Grodach, Carl, 11, 191
Habermas, Jürgen, 318
Hannigan, John, 49
Harding, David, 391n13
Harvey, David, 71, 126, 229, 387n2
Heckman, James, 402n1 (ch. 8)
Heelas, Paul, 202b, 203–5
Hemingway, Ernest, 8b, 140, 308
hierarchical linear modeling (HLM), 359–61, 362–63t, 368–69t
Hirschman, Albert, 398n18
Hoeckner, Berthold, 58b
Hotze, Tim, 403n18
hurdle models, 248f
income: Bohemian amenities and, 155; civic activities and, 258; county communitarian-urbanity scores, 156f;
inequality in metropolitan areas, 377t; political ideology and, 400n29; segregation, taste, style and, 376
individualism: American stress on, 79b; creative, 235
industrial districts, Marshall’s analyses of, 134
Inglehart, Ronald, 55
innovation: the arts and, 294–95; dimensions of, 153
international research, 324b; methodological challenges of, 381–83; neighborhood differences, 379–80
Jacobs, Jane, 224, 225, 244–45, 252b
James, William, 36, 36b, 204, 205b, 274
Jang, Wonho, 379–80
Joas, Hans, 197b
jobs: arts amenities and, 372–75, 375f; arts groups and, 192; changes, 283; collective intelligence and, 147b; county
communitarian-urbanity scores, 156f; entertainment-related, 228; quality of, 284; trends in, 179
Kaliner, Matthew, 176
Kallman, Meghan, 18b, 48b, 107b
Kant, Immanuel, 5, 54
karate: ethos of, 295; Martial Arts amenities and, 217f; New Age amenities and, 217f; New Con amenities and, 217f;
Pop Culture amenities and, 217f
Kaufman, Jason, 176
Kennedy, John F., 274
Knight, Frank, 137b
Knudsen, Brian, 398n17
Kotkin, Joel, 50, 183, 392n18
Kripal, Jeffrey, 204b, 394n35
LA-LA Land Tinsel, 62b; African American populations and, 394n31; artists and, 189; determinants of, 393n23;
income inequality and, 377; scene dimensions, 183; young people and, 185
land: concept of, 131; culturally infused meaning of, 122; Marx on, 127; return to, 129–35; value of place, 125–26
Landesman, Rocco, 295
landlords: capitalists and, 128b; interests of, 123–25
Latour, Bruno, 74–75b
Lazarsfeld, Paul, 172
Leach, Darcy, 244
leadership: citizen support for, 256; trust and, 231–32
legitimacy: amenity indicators, 101t; analytical dimensions of, 41t, 42t; coding of amenities, 336f; coding questions,
337t; dimensions of, 52–55; meaning and, 38; moral judgements and, 42–43; self-expression and, 269; traditional,
53b
leisure: consumption and, 11; social changes in, 11–12
Les Frigos (artist collective), Paris, 221, 222f
Levine, Donald, 211
Lévi-Strauss, Claude, 57
Lie, John, 47
Lipset, Seymour Martin, 77, 79b, 173, 254
Lloyd, Richard, 15, 45b, 60, 138, 348, 396n3
local authenticity: coding authenticity, 337t; description of, 30–31
location choices: crime rates and, 179; political orientation and, 179; political views and, 267–68; scene-like
qualities in, 177–80; young adults, 183f
Logan, John, 173, 376
Longworth, Richard, 159
Loop area, Chicago, 32, 164
Los Angeles, California: amenities, 93; charisma, 117f, 118; Community Redevelopment Agency, 297b; culture
formation of, 92b; ethnic bases of, 385–86n3; image of, 93; music industry, 161; neighborliness of, 107b, 113f;
respect for physical attractiveness in, 87b; scenes from, 105–6; self-expression, 113f; top amenities, 88–90t
Mao, Jefferson, 402n4 (ch. 7)
Markusen, Ann, 138, 150, 295
Marschall, Jörg, 49
Marshall, Alfred, 6–7; on factors of production, 123; influence on Parsons, 129–30; on the meaning of land, 122; on
rent, 133b; on town rents, 138b
martial arts: as a business, 394–95n37; demands of, 211; films involving, 210; as moral communities, 212b; social
bridges and, 208–12
Martial Arts amenities: correlation with other indexes, 216t; distribution of, 213–20, 214f, 214t; God and, 217f;
karate and, 217f; racial diversity and, 216t; top zip codes for, 215; yoga and, 217f
Martin, David, 199
Martin, John Levi, 31, 403n13
Martin Prosperity Institute (MPI), 310–11
Marx, Karl, 126–29, 128b, 387n1
McCloskey, Deidre, 6
McCraken, Grant, 6
McDonaldization, 49, 129
McRoberts, Omar, 391n13, 395n41
megachurches, 200b; desegregation of, 201b
Merleau-Ponty, Maurice, 6b
Merton, Robert K., 74b
Micallef, Shawn, 141b
migration: amenity-driven, 173; baby boomers, 188; context of, 256; European, 274; patterns for cities, 290–91;
patterns of, 257; the soul and, 174b; urban growth and, 290–91
Mihevc, Joe, 238
Miller, Diana, 400n30
“mind-body-spirit” activities, 205
Mockus, Antanas, 221
modeling contexts, 319–20, 350–67
Molotch, Harvey, 173, 174b
money: impact of, 236; political contexts of, 237t
Montesquieu, 255b
Montréal, Canada: entertainment district, 148; rationalism scores, 109f; rents, 382; self-expression scores, 109f; as
Sin City, 46b; traditional performance scores, 108
Moral Majority, 18, 198
Moretti, Enrico, 146b, 147
Moses, Robert, 245
Moynihan report, 174
Murdoch, James, 381
Murray, Charles, 196
music publisher distribution, 83
Muth, Richard, 370
Nagel, Thomas, 45
Nashville, Tennessee: amenities, 161; country music industry, 161
National Endowment for the Arts, 295
natural amenities: artists and, 189; compensation for lack of, 157b; USDA index of, 179, 390n21
Navarro, Clemente, 99, 171–72, 323, 378–79, 379f
Needham Lifestyle Survey data, 328, 330
neighborliness: charisma correlation with, 117–18, 117f; of Chicago, 107b; of Los Angeles, 107b; of New York,
107b; political ideologies and, 258; Republican counties and, 224; spatial patterns, 113f; theatricality and, 43–44,
100t
Neo-Bohemia, 45b, 60, 348, 390n17, 392n20
Nerdistan, 50–51; baby boomers and, 185; Communitarianism/Urbanity and, 392–93n22; growth in, 185; income
inequality and, 377; scene dimensions, 183; young people attracted to, 185
New Age amenities: correlation with other indexes, 216t; distribution of, 213–20, 214f, 214t; God and, 217f; karate
and, 217f; political culture and, 218; racial diversity and, 216t; yoga and, 217f
New Age index, components of, 212–13
“New Age” lifestyles, 198
New Age spirituality, 202–8
New Chicago School, 165–76, 323, 325
New Con amenities: correlation with other indexes, 216t; distribution of, 213–20, 214f, 214t; God and, 217f; karate
and, 217f; racial diversity and, 216t; top zip codes for, 215
new social movements (NSMs): activist, 398n16; American context of, 244; crime rates and, 397–98n15;
Democratic voters and, 397–98n15; influence of, 243; local contexts of, 248f; locations for, 247–50; nature and,
242; politics, aesthetics and, 242–54; rents and, 397–98n15; self-expression and, 252–53, 253f; top zip codes for,
247t; urbanity factor scores and, 249f; walkability and, 252–53, 253f
New York, New York: art galleries, 91; cafes in, 91; charisma, 117f, 118; coffeehouses, 91; ethnic bases of, 385–
86n3; Lower East Side, 140; music industry, 161; neighborliness of, 107b; nightclubs, 91; political organizations,
386n4; radicalism in, 91b; scenes from, 105–6; top amenities, 88–90t
Nicodemus, Anne Gadwa, 295
Nietzsche, Friedrich, 245b
nightlife, economic meanings of, 136b
Norris, Chuck, 210, 211
Novak, Jennifer, 402n2 (ch. 7)
Obama, Barack, 18, 223
Obama-McCain election, 260
Paris, France: Bohemian quarters, 59; cultural styles, 379
Parsons, Talcott, 122, 129–30, 135, 388n6
Patillo, Mary, 66b, 162
Patterson, Orlando, 174, 391n9
Pebble Beach, California, 275b
Pentecostal churches, 219
Pentecostalism, 199
performance scores of scenes: aggregating amenities and, 98–99; analytical independence of, 345–47; calculation of,
99, 341f; combination of, 342–44; computation of, 338–42; economic development and, 151f; factor score
weights for, 343f; self-expression, 366t; spatio-cultural relationships and, 106–19; using various radii, 366t
Peterson, Richard, 31, 396n4
place, 1–2, 68, 135, 230
political contributions: Blue Blood index and, 277f; scenes and, 272–78
political culture: authenticity and, 101t, 234; autonomy and, 270–72; “buzz” and, 231–32; context and composition,
267–68; effects of scenes on, 17–18; geographic patterns, 262; integration and, 270–72; local and national, 235;
local dynamics of, 302; neighborhood choices and, 196; new, rise of, 229; New Age amenities and, 218; patronclient type, 236; patterns of, 223; polarization and, 270–72; quality of life demands and, 232; rents and, 267f;
subcultures in, 257; transgression and, 265–66, 267f
politics: elite-centric analysis, 255–56; national, 254–78
Pop Culture amenities, 165; correlation with other indexes, 216t; distribution of, 213–20, 214f, 214t; God and, 217f;
karate and, 217f; racial diversity and, 216t; top zip codes for, 215; yoga and, 217f
Pop Culture index, components of, 212–13
population changes: county communitarian-urbanity scores, 156f; gentrification and, 195–200; location decisions
and, 177–80; subgroups and, 184–88; walkability and, 158b
Postrel, Virginia, 44b
Potts, John, 52
Pradelle, Michèle de la, 47
Protestant Reformation, 159–60
Pullman Town, 166
Putnam, Robert, 8, 74, 81, 198, 228, 262–63, 289
quality of life: local development and, 232; quality of place and, 230
quasi-rents, 133–34
race: bridges across, 13; political ideology and, 260
racial diversity: growth in, 200, 395n39; Martial Arts amenities, 216t; New Age amenities and, 216t; New Con
amenities and, 216t; Pop Culture amenities and, 216t
racial segregation, 354–55
Rakove, Milton, 46, 118b, 167b
rationalism: scores, 109f; score weighting of amenities, 110–11t; spatial patterns, 112–14; Toronto vs. Montreal,
109f
rationality, 49–52, 101t
recreation sector: employment trends in, 12f; growth of, 11
religion, political ideology and, 261
Renoir’s Loge (Theater Box), 148–50; economic development and, 149f; key amenities, 148b; scenes, 61b
rents: of ability, 134; absolute, 387n2; as analytical category, 133b; artists and, 189; determination of, 387n1;
differential, 387n2; gentrification and, 189; glamour dimension and, 150; Republican vote scores and, 267f; scene
dimensions and, 382; self-expression and, 150
Republican counties: blue bloods and, 275; communitarian dimensions and, 224; dimensions of, 258; predictors for
vote outcomes, 261f; Rossini’s tour and, 401n39; scenes and, 259f, 260f, 261–62
residential decisions: conflicts in, 235; job-based, 164; racial segregation and, 196–97; scene-driven, 13
residential effects, scenes, 10–19
residential patterns, shaping of, 162–220
retirees: healthy aging, 296–97b; location choices by, 187f, 188; marketing to, 162–63; scene choices by, 13, 180–82
Ricardo, David, 122, 125–26
Rossini’s Tour, 62–63b; artists and, 189; Blue Blood amenities and, 401n39; boomers in, 185; income inequality
and, 377; scene dimensions, 183; young people and, 185
Rothfield, Lawrence, 323
ruppies (retired urban professionals): lifestyle of, 14b, 162; parties, 15b
rural-urban divide, 86, 258
Samuelson, Paul, 256
Samurai’s Licensed Quarters, The, 61b
Sandel, Michael J., 129, 130b
San Francisco Bay area, California: new social movements in, 247; “Pavement to Parks” program, 306–7b
Sassen, Saskia, 229
Sawyer, Stephen, 18, 68, 379, 381
scene policy, principles of, 315–17
scenescapes: as aesthetic view of place, 1–2; altered by surroundings, 139; amenities and, 95–103; combinatorial
logic of, 56–66; composition of, 32–35; delineation of, 9–19; as dependent variables, 375–78; dimensions of, 43–
55; embedded meanings of, 2–4; emergent properties of, 346; impact of differences in, 144; impermanence of,
328; international context for, 378–83; measurement of, 66–69, 332–44; multiple complex, 182–84; national
politics and, 254–78; overview of international research, 324b; perception of, 2–19; power of, 221–79; public
policy thinking and, 280–317; recognition of, 4–9; residential effects of, 10–19; residential patterns, 162–220;
self-expressive, 25f; spatial patterns in, 112–14, 113f; stability of, 346–47; standard model of, 319, 332–33; theory
of, 29–69, 342
scenes data sets: analysis of trends using, 328; comparability, 326–27; data sources, 328–32; differentiation of
amenities in, 327; ideal, 326–28; spatial resolution of, 327
scene variables, construction of, 104
scenius, 137b
Scerri, Eric, 21
Schumpeter, Joseph, 123
score weighting of amenities, 110–11t
self-expression: adjacent scenes and, 356; charisma correlation with, 117–18, 117f; college grads and, 304f; conflict
and, 303–4; Democratic votes and, 224; economic growth and, 145f, 151f; glamour and, 151–54; growth impacts,
389n14; individual, 235; legitimacy and, 54–56, 101t, 269; local authenticity and, 185; local development and,
232; location choices by seniors, 181f; married couples and, 391n13; martial arts and, 210–11; neighboring
transgressiveness and, 356–57; new social movements and, 249; performance scores, 366t; political salience of
walkability and, 251–54; population density and, 143; religious communities and, 206–7; scenes supporting, 139;
score weighting of amenities, 109f, 110–11t; spatial patterns in, 112–14, 113f, 355; technology clusters and, 144–
47, 145f; Toronto vs. Montreal, 109f; walkability and, 252–53, 253f
self-spirituality, 202b; roots of, 203–4
Seman, Michael, 11, 191
Sennett, Richard, 196, 244
Seoul, Korea, 379–80
Silicon Valley, 87b
Simmel, Georg, 38, 56, 86
situation value, 134
small towns, political ideology and, 259
Smelser, Neil, 130, 135
Smith, Adam, 122, 122f, 124–25b, 246b
Sombart, Werner, 168
Sontag, Susan, 65b, 171
Soulman statue, 162, 163f
spatial adjacency, among scenes, 350
spatial dependence, modeling of, 353–54
spatial patterns, in scenes, 112–14, 113f
spatial relationships: adjacency and, 405–6n36; operationalizing of, 365f
spatio-cultural relationships, 106–19
state, authenticity and, 47–48, 101t
Stephen Fry in America, 70–72
Stinchcombe, A. L., 396–97n6
Stone, Clarence, 396n4
Taylor, Charles, 8, 40b, 160
technology clusters, 388–89n11; county communitarian-urbanity scores, 156f; economic growth and, 145f; selfexpression and, 25f, 144–47, 145f
theatricality: amenity indicators, 100t; analytical components of, 41t; analytical dimensions of, 42t; coding
questions, 337t; dimensions of, 43–46; formality and, 45; meaning and, 37–38; performance and, 41–42
“the Core”: contents of, 405n29; definition of, 345
Thompson, John, 68, 170b, 391n8
Tiebout, Charles, 398n18
Tocqueville, Alexis de, 76–77, 256b
Tönnies, Ferdinand, 57, 115, 116b
Toronto, Canada: economic changes in, 305–7; employment changes in, 309f; entertainment district, 148; expressive
culture in, 305–8; expressive revolution in, 8b; growth of, 306–7; rationalism scores, 109f; reindustrializing, 311;
rents, 382; self-expression scores, 109f; traditional performance scores, 108; transgression scores, 386–87n9;
waterfront, 300
traditionalism: antitraditional scenes, 112; by Canadian FSAs, 108f; charisma correlation with, 117–18, 117f;
economic growth and, 151f, 153; political ideologies and, 258; Republican counties and, 224; resistance by cities,
109–14; self-expression and, 303–4
transgression: ambiguity of, 250–51; Democratic votes and, 224; location choices and, 181f; other dimensions
versus, 105f; political ideology and, 263; political meaning of, 398n16; Republican vote scores and, 265–66, 267f;
theatricality and, 44–45, 100t
trust, leadership and, 231–32
university graduates: county communitarian-urbanity scores, 156f; impact of artist concentration on, 150; natural
amenities and, 158b
Urbanity: artists and, 189; baby boomers and, 185; Communitarianism versus, 115; dimensions of, 397–98n15; of
young people, 185
urban policy: arts, culture and, 289–90; challenges for, 281–92; globalization and, 281–82; higher-level, 294–300;
local-level, 300–303; new directions in, 293–305; principles of, 315–17
utilitarianism: legitimacy and, 53–54, 337t; spatial patterns, 112–14
Veblen, Thorstein, 376, 393n23
Vivekananda, Swami, 394n36
voting: political contexts of, 237t; presidential elections and, 257–66, 260f; turnouts, 399n24
Wagner, social science and, 57–59
Wagner’s Volk, 65b
walkability: authenticity and, 289; definition of, 390n20; political salience of, 251–54; self-expression and, 252–53,
253f; urban policy and, 302
walkable places, 142; local authenticity and, 158b; new social movements and, 224
Weber, Eugen, 47
Weber, Max, 38, 131, 159–60, 369; ideal types, 57; influence on Parsons, 129–30; on inner-worldly activists, 199;
on the meaning of land, 122
West Queen West, Toronto, 312; artist-led change in, 191; scene, 32
Wicker Park, Chicago: artist-led change in, 191; ethnography, 15; scene, 32
Williamsburg, Brooklyn, 191
Wilson, Elizabeth, 16b, 60b, 64, 250b
Wilson, James Q., 61b
Wilson, William Julius, 174, 391n9
Wirth, Louis, 106
Wittgenstein, Ludwig, 35b
Wolfe, Thomas, 47
Wolff, Robert Paul, 129
World Values Survey, 226–27t, 228
Wright, Richard, 162
Wychwood Barns, Toronto, 237–42, 397n7
Yáñez, Navarro, 272
yellow pages (YPs): amenities, nationally, 78t; amenities by kurtosis, 82t; amenities by region, 84–85t; amenity
counts using, 76; data from, 72–76, 328–32, 403n18; descriptive statistics from, 331f; top amenities by city, 88–
90t
Yi, Joseph, 200, 208, 210b, 212b, 295
yoga, 203; as a business, 394–95n37; history of, 394n36; Martial Arts amenities and, 217f; New Age amenities and,
217f; the New Age index and, 212–13; New Con amenities and, 217f; Pop Culture amenities and, 217f; top zip
codes for, 80–81t; variants of, 206–7
young people: location choices, 181f, 183f; marketing to, 162; scene choices by, 180–82
Zelizer, Viviana, 209b
Zukin, Sharon, 47, 140