Consumer Cities, Scenes, and Ethnic Restaurants

Abstract

This chapter builds on past work to examine the distinctive ways in which ethnic restaurants help to define the contemporary scenescape in US cities. It uses the example of restaurants to illustrate how to apply and extend a scenes approach. Restaurants in general and ethnically themed restaurants are crucial components of many cities and communities' consumer offerings. They often make the scene. After briefly reviewing some general principles of the scenes perspective, the authors discuss ethnic neighborhoods and the role of consumption venues such as restaurants in defining their identity. The authors stress multiple ways that ethnically themed amenities and local populations may overlap in various contexts, as well as how they can join with other dimensions of local scenes. These ideas are illustrated by examining multiple types of ethnic restaurants across all US zip codes, paying particular attention to the degree to which they correspond with coethnic residential populations, and how this varies by group and city. The authors also investigate the types of scenes typical of cosmopolitan areas that offer diverse ethnic cuisines.

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Subject: Sociology, Economic Sociology Online Publication Date: Feb 2019
DOI: 10.1093/oxfordhb/9780190695583.013.31
Consumer Cities, Scenes, and Ethnic Restaurants
Daniel Silver and Terry Nichols Clark
The Oxford Handbook of Consumption
Edited by Frederick F. Wherry and Ian Woodward

Oxford Handbooks Online
Abstract and Keywords
This chapter builds on past work to examine the distinctive ways in which ethnic
restaurants help to define the contemporary scenescape in US cities. It uses the example
of restaurants to illustrate how to apply and extend a scenes approach. Restaurants in
general and ethnically themed restaurants are crucial components of many cities and
communities’ consumer offerings. They often make the scene. After briefly reviewing
some general principles of the scenes perspective, the authors discuss ethnic
neighborhoods and the role of consumption venues such as restaurants in defining their
identity. The authors stress multiple ways that ethnically themed amenities and local
populations may overlap in various contexts, as well as how they can join with other
dimensions of local scenes. These ideas are illustrated by examining multiple types of
ethnic restaurants across all US zip codes, paying particular attention to the degree to
which they correspond with coethnic residential populations, and how this varies by
group and city. The authors also investigate the types of scenes typical of cosmopolitan
areas that offer diverse ethnic cuisines.
Keywords: scenes, place-making, urbanism, neighborhoods, ethnicity, food
Cities have become focal points of the postindustrial economy. Heavy industry employs
fewer workers, while the service sector has grown. A host of personal services and
consumer amenities has increasingly come to define the urban landscape: coffee shops,
restaurants, art galleries, yoga studios, gyms, bars, nightclubs, and the like. Such
services and amenities tend to require interpersonal interaction and physical co-
presence; they are difficult to outsource. Former production spaces such as warehouses
and factories become repurposed as event spaces, and they may themselves be
appreciated as amenities contributing to a distinctive urban aesthetic.
No longer a generic residual to production, “consumption” becomes an active process
with multiple dimensions. What and how to consume become more salient, not only
whether and how much. As consumption opportunities expand and concentrate, cities and

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neighborhoods increasingly come to be defined by the overall set of amenities they offer
rather than by any single amenity. Not only this swanky restaurant or that designer
clothing store, this tattoo parlor or that punk music venue, this locally sourced butcher
shop or that microbrewery est. 1972, but the holistic ambiance they combine to produce:
a sense of glamorousness, or local authenticity, or transgressiveness. They become
scenes.
“The scenes project” (https://scenescapes.weebly.com) is a loose collection of
international collaborators who have been studying the nature, sources, and implications
of scenes. Researchers from the United States, Canada, France, Poland, Korea, China,
Japan, Spain, and beyond have sought to articulate a “scenes perspective” for studying
cities and communities, document varieties of scenes, and examine how they intertwine
with local economic development, residential patterns, and politics. Scenescapes: How
Qualities of Place Social Life (Silver and Clark 2016) brought together much of this
research, highlighting the United States and Canada while pointing toward related
significant work elsewhere.
This chapter builds on this past work to examine the distinctive ways in which ethnic
restaurants help to define the contemporary scenescape in US cities. It uses the example
of restaurants to illustrate how to apply and extend a scenes approach. Restaurants in
general and ethnically themed restaurants are crucial components of many cities’ and
communities’ consumer offerings. They often make the scene.
After briefly reviewing some general principles of the scenes perspective, we (again
briefly) discuss ethnic neighborhoods and the role of consumption venues such as
restaurants in defining their identity. We stress multiple ways that ethnically themed
amenities and local populations may overlap in various contexts, as well as how they can
join with other dimensions of local scenes. We illustrate these ideas by examining
multiple types of ethnic restaurants across all US zip codes, paying particular attention to
the degree to which they correspond with coethnic residential populations, and how this
varies by group and city. We also investigate the types of scenes typical of cosmopolitan
areas that offer diverse ethnic cuisines.
Overall, we find a wide variety of patterns, and we note in particular that some cities such
as Chicago and Los Angeles stand out in sustaining strong linkages between ethnic
amenities and ethnic populations in general, while other cities specialize in particular
groups, and still other areas have ethnically themed scenes without a correspondingly
concentrated ethnic residential population. Neighborhoods with cosmopolitan restaurant
scenes tend to be young and racially diverse, and they seem to some degree to defy
standard gentrification narratives. There is no one true model of ethnic scenes, but a
plurality of options that emerge in different forms in different contexts.

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A Brief Introduction to the Scenes Perspective
As cities and neighborhoods become increasingly defined by the opportunities for
consumption that they offer, it becomes correspondingly important to examine them from
the point of view of a consumer. It is from this standpoint that a place appears as a scene.
This is not the only way to encounter an area, and contrasting multiple other orientations
can provide a useful point of comparison, as in Table 1.

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Table 1. Contrasting Cultural Scenes, Residential Neighborhoods, Political Arenas, and
Industrial Clusters
Orientation
to Place
Cultural
Scene
Residential
Neighborhoo
d
Industrial
Cluster
Political
Arena
Activities Expressing
and
communicatin
g feelings,
experiences,
moods
Securing
necessities,
basic
services,
housing,
schools,
safety,
sanitation,
community
development
Work,
production
Collective
action
Agents Consumers Residents Producer Citizen/
leader/
officials/
activist
Physical
Units
Amenities Homes/
apartments
Firms Power centers
Basis of
Social Bond
Lifestyles/
sensibilities
Being born
and raised
nearby, long
local
residence,
heritage
Work/
production
relations
Ideology,
party, issues,
citizenship

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Table 1 lays out several ways of encountering a place. As a producer, it is a place to work,
and one treats the environment as a set of firms. As a resident, it is a place to live, and
homes are the relevant units. As a political actor, it is a place for collective action, and the
goal is to generate and mobilize power. As a consumer, it is a place to take in and
experience, and the space appears as a collection of amenities. It is a scene.
All of these modes of encounter coexist and overlap, enabling the same object to appear
in different modes. For example, an office tower, bar, or factory can be—even for the
same individuals—places to work and amenities to be appreciated or rejected, whether as
symbols of power, neighborly warmth, or ruthless efficiency. When we adopt a scenes
perspective, we take this consumer point of view as a starting point and treat cities and
communities in terms of how they may be appreciated.
One major theoretical contribution of scenes researchers has been to articulate a range
of standards of taste according to which they may be judged. Drawing on diverse sources
such as social theory, literature, journalism, philosophy, poetry, and beyond, we often
work with a set of fifteen dimensions of meaning that are useful for describing scenes,
grouped into three broad classes. These dimensions highlight how scenes offer forms of
(1) theatricality, or ways of seeing and being scene, for instance glamorously,
transgressively, or in a neighborly or formal way; (2) authenticity, or notions of what is
genuine or fake, such as locality, ethnicity, or corporateness; (3) legitimacy, or notions of
what is a valid authority, such as tradition, charisma, utility, or personal self-expression.
Tables 2 and 3 lay out these dimensions, which we often describe as a kind of conceptual
bricolage—a way of joining conceptual bits from the history of social and cultural thought
into a bundle of tools available for the scenes researcher to use and adapt as needed.
Table 2. Analytical Components of Scenes I: Theatricality, Authenticity, and 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
Table 3. Analytical Dimensions of Scenes II: Dimensions of Theatricality, Legitimacy,
and Authenticity

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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 Anti-state
Ethnic Nonethnic
Corporate Independent
Natural Artificial
Rational Irrational
Scenescapes, ch. 2 elaborates these dimensions in more detail. Together, they provide a
matrix for identifying the qualitative character of a scene as a combination of these
dimensions. One area may join self-expression, transgression, exhibition, and anti-
corporateness, and it could in this way approach a bohemian scene. Another could join
self-expression, neighborliness, and local authenticity, as in a quaint arts-oriented
community such as Carmel, California, or Asheville, North Carolina. In this way, the

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scenes perspective features combinatorial and holisitic thinking: a holistic scene such as
Bohemia may be articulated as a combination of dimensions, which may be found in
different levels and configurations elsewhere, making it possible to identify and compare
subtle variations in scenes amid broader commonalities. Wagner’s approach to opera
provides a major inspiration for this approach to social analysis, as a weaving together of
Leitmotifs, as Levi-Strauss pursued in Mythologiques.
The aspects of place distinguished in Table 1 are not distinct; they may feed into one
another. This mutual influence provides a key analytic lever that organizes much scenes
research. For example, in Scenescapes, we develop general and specific propositions
about how scenes feed into (a) economic development, (b) residential patterns, and (c)
politics. Drawing on multiple data sources, we show how the impact of technology
clusters on economic growth is enhanced when they are located in scenes that evince the
value of personal self-expression; how different demographic groups gravitate to scenes
that feature different dimensions (young people to more transgressive scenes, baby
boomers to scenes that combine local authenticity and self-expression); and how national
presidential voting patterns increasingly divide between more “urbane” scenes (strong in
self-expression, glamor, transgression, and rationalism) and more “communitarian scenes
(strong in tradition, neighborliness, and formality). Other researchers have pursued
similar lines of analysis in other contexts (Buin et al. 2011; Navarro 2012; Navarro,
Mateos, and Rodriguez 2012; Sawyer 2011).
Ethnic Neighborhoods, Multicultural Cities,
and Amenities
While the main thrust of scenes analysis is to feature holistic combinations of many—
often hundreds—of various indicators, it is often also important to drill down and examine
specific types of amenities that resonate with ongoing critical discussions. Thus, for
example in Scenescapes (ch. 5), to examine questions about America’s cultural divisions
and potential bridges across them, we investigate location patterns of “new conservative”
churches (e.g., Pentecostal, Seventh Day Adventist, etc.), “new age” amenities (e.g., yoga
studios, meditation centers, and the like), and martial arts studios, along with “pop
culture” amenities (e.g., fast food, music, movies). We find that while American
communities are rather sharply divided between the first two, the latter two are more
broadly shared, and martial arts in particular stand at a particularly intriguing nexus
within the various crosscutting cleavages of the American cultural matrix (see also Yi and
Silver 2015).
In a similar way, here we examine ethnically themed amenities, in particular restaurants.
There are a number of reasons for doing so. Racially marginalized persons have been
featured as key components of some scenes at least since the Parisian bohemians of the
nineteenth century. They sought scenes defined by outsiders and outcasts, and took the
presence of marginalized groups as signs of this kind of scene. Similar attitudes persisted
among the “neo-bohemians” featured in Richard Lloyd’s (2010) studies of Chicago’s

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Wicker Park in the 1990s, in which nonwhite residents and ethnic amenities (shops,
restaurants, and the like) fed into images of a gritty authenticity that stood outside of the
whitewashed conformism and standardization of the (stereotypical) suburban office park
or global corporate workplace.
In these versions, the starting point is a putative “nonethnic” observer for whom the
“ethnic character” of a scene is somehow attractive (or repulsive, as the case may be).
While this point of view persists in some quarters, it is partial. A somewhat more complex
picture arises, however, if we (briefly) consider the role of the “ethnic neighborhood” in
American cities historically, and also in the context of contemporary “multicultural” cities.
The literature on ethnic neighborhoods is, of course, massive, and we make no claim to
anything approaching a comprehensive review. For present purposes, a few key points
suffice. Ethnic neighborhoods are often associated with immigrant settlement processes.
They provide familiarity, social support, key information, job prospects, cultural identity,
and more (Hou and Picot 2004; Massey and Denton 1985; Qadeer, Agrawal, and Lovell
2010; Wilson and Portes 1980). Key amenities solidify the neighborhood in this role, such
as churches, festivals, parades, shops, and restaurants. In this way, the familiar American
pattern emerges—with early twentieth-century Chicago as a classic case in point—in
which the city forms a patchwork of ethnic communities, with their own distinct customs
and style of life. Here, distinctive ethnic groups—Irish, Polish, Lithuanian, Italian, and so
on—lived not near factories but instead built and lived near their own parishes; they often
worked far away from their homes, and their identities were correspondingly shaped less
by the workplace and more by ethno-cultural factors. If Chicago was an extreme case,
many other cities have collections of Greektowns, Chinatowns, Little Koreas, and other
ethnic neighborhoods, perhaps increasingly so (Logan, Zhang, and Alba 2002).
Insiders and outsiders alike readily observe these differences. They provide key bases for
a broader sense of the importance of pluralism and context in understanding social
processes. For example, 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. This contrasted to
the typical Marxian approach, which was to envision old ways of living together being
swept into the dustbin of history as economic affiliation overwhelmed other sources of
identity. The Chicago approach is more pluralistic and pragmatist: the strength of
different types of social bonds varies in different local situations.
Some observers, academic or otherwise, expected ethnically distinctive areas to fade as
immigrants assimilated into the WASP majority culture (Brubaker [2001] reviews these
debates about “assimilation”). In some cases this did occur; for instance, many German
Americans actively sought to downplay their German heritage in the wake of World War I
(Conzen 1979), including rebranding local businesses. Yet for many groups—including

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African Americans, Hispanics, and Asians—“spatial assimilation” has been a very uneven
process (Qadeer 2016:132). It varies by country (see Walks and Bourne 2006 on US/
Canada differences), but cities also play a role.
The history of cities like Chicago or Boston again provides a major case in point. Here
and elsewhere, many immigrant groups proudly retained overt markers of their ethnic
identities even as in other ways they integrated into major institutions of American life,
such as city politics and corporations. The neighborhood again proved crucial, often as a
symbolic focus (Conzen 1979; Gans 1982; Kantowicz 1975; see Waters 1990 on symbolic
ethnicity in general). Even as many individuals moved to the suburbs or mixed urban
neighborhoods, the concentration of amenities provides meeting points at nights or on
weekends, and festivals and parades offer opportunities for periodic renewal and
affirmation. The “ethnic” dimension of the urban scene becomes less (or not only) an
exotic sign of transgression but a regular component of urbanity. As cities create
opportunities for a critical mass of “unconventional” subcultures to coalesce (Fischer
1995), more individuals become more comfortable experimenting with unusual (to them)
cuisines or styles of dress.
These and other processes pluralize the traditional close correlation between a particular
residential population with a common ancestry and a corresponding set of local
amenities. Ethnicity itself can become a target in efforts to brand or shape the public
perception of a neighborhood, yielding multiple possible configurations. For example,
Hackworth and Rekers (2005) show four just in Toronto: in the Corso Italia neighborhood
there remains a strong overlap of Italian ancestry and Italian amenities frequented by
Italian Canadians, whereas Little Italy has few Italian residents and many Italian
restaurants that cater to non-Italian diners, tourists or otherwise; Greektown has seen its
Greek Canadian population decline, but remains a focal point for Toronto’s Greek
community, primarily through the efforts of an active local business association; Little
India too remains strongly identified with Indian cultural identity and a center for
shopping and dining, even though from its inception there were few local residents of
Indian ancestry. Wherry (2011) identifies the subtle Puerto Rican art, culture, and
cuisine, for example decorating children’s faces for a parade, and featuring guitar songs
on a bus, showing how these can be both a source of internal ethnic pride and a proud
cultural artifact to display to tourists. Acknowledging yet not fearing the tourist’s gaze in
this respect is a step toward cosmopolitanism—it can enhance the theatricality of urban
life, while retaining a sense of ethnic authenticity. In these and many cases elsewhere, the
retail, amenity, and general consumer landscape can become a point of contestation, as
various groups struggle to retain or acquire control of the neighborhood’s public
reputation (Light 2002; Martinez, 2017).Thus, we should expect correlations between
ethnic residential populations and ethnically themed amenities (such as restaurants) to
vary, in multiple ways, for instance by the particular group in general, by various groups’
historical relationships to particular cities, and by particular cities which foster ethnic
neighborhoods as an organizing principle. Yet beyond variation in these correspondences
between specific groups and “their” amenities, it is also worth considering the

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phenomenon of the “multicultural” neighborhood as well. Here again the ethnic
restaurant plays a key role.
“Multicultural cities,” according to Mohammad Qadeer (2016), join both particularity and
commonality. They are dotted with ethno-culturally distinct neighborhoods but also have
a “common ground” that permits mutual interaction, shared rules of the game, and
reasonable accommodation. An important feature of this (complex) common ground is
cosmopolitan areas, in which the consumption of variety itself predominates. “This form
of everyday multiculturalism widens the range of common norms and behaviors”(Qadeer
2016:157; see also Elijah Anderson’s (2011) notion of the cosmopolitan canopy (2011).
Restaurants are central to the multicultural consumption of variety: “a multicultural city
is distinguished by the choice of cuisines it offers” (Qadeer 2016:157). This is heightened
in food courts and commercial streets in which not one but many different cuisines are
simultaneously on offer and contribute to dynamic, offbeat scenes often attractive to
more educated and cosmopolitan young people. Such neighborhoods are not restricted to
North America, as for instance Kim (2016) shows in a study of Seoul’s Itaewon
neighborhood. Thus, we would expect areas with a diverse variety of cuisines to be
located in multiethnic, young, dense, urbane neighborhoods with more funky scenes and
numerous college graduates.
Data and Methods
These sorts of issues about the interplay of consumption and local populations are often
pursued in close case studies of one or a few neighborhoods, which more synthetic work
then sometimes reviews and seeks to join. There is great value in this approach, and we
sometimes pursue it ourselves. It is nevertheless useful to also take a more synoptic point
of view, and seek to consider these bigger conceptual mappings with broad-based
empirical claims that simultaneously compare many groups and local areas to one
another by a common set of metrics. This sort of thin description may not yield the same
depth of understanding of the intricacies of local dynamics as its thicker cousin. But it
may still help to determine the extent to which local observations hold generally, identify
outliers and typical forms for further investigation, and establish commonalities and
differences across groups and cities. To converse with ethnographic, single-city thick
descriptions, we start with key empirical findings and then return to bigger conceptual
themes.
To pursue this sort of broad synoptic overview, we utilize two main data sources. One is
the US Census, which asks respondents about their “ancestry.” For this analysis, we used
data from the 2000 Census, but it would be interesting to examine other years to
investigate changes. The other is our database of local amenities, downloaded from online
business directories (e.g., yellow pages), and described in more detail in Scenescapes (ch.
8 and appendix). It includes dozens of restaurant categories, often explicitly labeled in
ethnic terms, such as “Greek restaurant” or “Chinese restaurant,” and covers all US zip
codes. Our analysis matches eleven ancestries and cuisines: African American (soul food),

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Chinese, Cuban, French, German, Greek, Irish, Italian, Japanese, Korean, and Mexican.
We use these two sources to construct a national measure of zip code restaurant variety
based on fifty-three types of cuisines, and to examine its association with a host of census
variables (e.g., rent, population density, racial diversity, college education, young people)
and our measures of more holistic scenes (e.g., those that prize urbanity, glamorousness
and self-expression, locality, and so on). More details about specific variables and
methods appear later, in the text and in notes to tables and figures.
Our analysis proceeds in three main steps. First, for each group separately we identify
counties in which the (zip code) correspondence between ancestry and restaurant is
strongest and weakest. Second, we compare groups to one another, determining (a)
groups for which the ancestry/restaurant correspondence is strongest or weakest in
general; (b) selected counties in which specific ancestry/restaurant correlations are
especially striking; and (c) counties in which ancestry and restaurant tend to strongly
overlap in general, regardless of the specific group. Third, we examine zip codes with
diverse restaurant offerings and determine the types of scenes of which they are typically
a part.
The analysis illustrates how to apply and extend general principles of scenes thinking. For
instance, we stress how core sociological concepts like ethnic or multicultural
neighborhoods may be decomposed into configurations of multiple overlapping variables,
whose combinations we can systematically examine. We also stress context, showing how
the “same” variables operate differently in different situations. Similarly, we connect
particular amenities such as restaurants to broader meanings embedded in the localities
of which they are part, such as glamour or urbanity. This interplay of the particular and
the general is a hallmark of scenes analysis, as is the effort to examine localities in terms
of the meanings they evoke. Researchers may follow the model of the analysis to develop
similar analysis in other arenas.
Analysis
We first examine each group separately, identifying where the relationship between
restaurants and ancestry is strongest for each. To do so, we fit a series of multilevel
models, one for each group. In each model, the dependent variable is the proportion of
the zip code population that reports a given background (e.g., proportion of the total zip
code population that is African American, Chinese, Cuban, etc.). The independent
variable is the number of each restaurant type per total amenities of all types (some 375
in our yellow pages database) in the zip code, which we refer to simply as “restaurants.”
At this stage of the analysis, the restaurant “random slopes” are our main interest. They
indicate counties in which the relationship between restaurant and ancestry is stronger
or weaker than the US average. Table 4 summarizes some key findings. The numbers in
parentheses show the approximate total number of counties for which the restaurant–
ancestry relationship is statistically significant, and the columns list the top five counties

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for each group. Counties in bold have a substantial break between them and other
counties, potentially indicating cities with qualitatively distinct ethnic neighborhoods.

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Table 4. Counties with Strong Ethnicity/Restaurant Overlaps for Various Groups
African American Chinese Cuban
Positive
(9)
Negative
(20)
Positive
(23)
Negative
(0)
Positive
(4)
Negative
(0)
Genesee,
MI
Philadelphi
a, PA
San
Francisco,
CA
Hudson,
NJ
Cook, IL Polk, FL Alameda,
CA
Dade, FL
New
Castle, DE
Mercer, NJ San Mateo,
CA
Palm
Beach, FL
Westcheste
r, NY
St. John
the
Baptist, LA
Santa
Clara, CA
Monroe,
FL
Wayne, MI Fort Bend,
TX
Honolulu,
HI
French German Greek
Positive (0) Negative
(85)
Positive (0) Negative
(0)
Positive (6) Negative
(0)
Essex, VT Queens,
NY
Aroostook,
ME
Pinellas,
FL
Coos, NH Fairfield,
CT
Franklin,
NY
Hampden,
MA
Orleans,
VT
Cook, IL

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Irish Italian Japanese
Positive (2) Negative
(0)
Positive
(39)
Negative
(5)
Positive
(11)
Negative
(1)
Suffolk,
MA
Essex, NJ Atlantic,
NJ
Honolulu,
HI
New York,
NY
Nassau,
NY
Philadelphi
a, PA
Barnstable,
MA
Hawaii,
HI
Richmond,
NY
Northampt
on, PA
Kauai, HI
Bronx, NY Salem, NJ Maui, HI
New
Haven, CT
Dare, NC Los
Angeles,
CA
Korean Mexican
Positive
(17)
Negative
(0)
Positive
(75)
Negative
(12)
Queens,
NY
Los
Angeles,
CA
Marin, CA
Bergen, NJ Cook, IL Colusa, CA
Los
Angeles,
CA
Kane, IL Sonoma,
CA
Orange,
CA
Santa
Cruz, CA
Brazoria,
TX
Anchorage,
AK
Maverick,
TX
Mesa, CO
Note. While we use multilevel statistical analysis and refer to independent and
dependent variables, we generally do not seek to impute atomistic causal
interpretations. Rather, a core focus of scenes analysis is how variables join into

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gestalts, which we explore with many methods, including case studies and participant
observation. This table summarizes eleven separate multilevel models, one for each
group. In each model, ancestry is the dependent variable and the corresponding
restaurant type is the independent variable. The table highlights counties in which the
relationship between restaurant and ancestry is particularly strong or weak. Numbers
in parentheses indicate the approximate number of counties in which the restaurant–
ancestry relationship is statistically different than average. For readability, the table
only lists the top five counties for each group. Bold indicates counties in which the
relationship appears to be substantially stronger or weaker than elsewhere. We
include restaurants as a level 1 fixed effect and as a varying slope within counties,
which are a level 2 grouping variable.

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Much could be said about Table 4, but here we restrict the discussion to some major
themes. The table demonstrates that this simple technique can identify ethnic
neighborhoods in which a local population and a corresponding set of amenities create a
strong and recognizable community identity: San Francisco’s Chinatown, “Havana on the
Hudson,” Koreatown and (Greek) Astoria in Queens,1 distinctive Mexican enclaves in Los
Angeles and Chicago, Japanese communities in Hawaii, or Chicago’s centers of African
American culture such as Bronzeville. It shows that European ethnic groups continue to
maintain a spatial relationship to “their” amenities in some places, such as Italians in
New Jersey or Irish in Boston (Suffolk County), even as others, especially French and
German, have largely become more spatially dissociated.
We also find evidence of how widespread or narrow the ancestry–restaurant relationships
are for different groups. For example, over seventy counties have especially strong
overlaps between Mexican populations and Mexican restaurants, around forty for Italian,
and twenty for Chinese and Korean. Counties in which Greek or Irish overlaps relatively
strongly with corresponding restaurants are rarer. Thus, one has more opportunities to
find “authentic” restaurants embedded in corresponding residential populations in more
parts of the country for the former group than the latter.2
At the same time, this technique identifies where the relationship between restaurant and
a corresponding local population is relatively weak. For example, the negative
relationship between Japanese restaurants and ancestry in Manhattan indicates
Manhattan’s position at the leading edge of the diffusion of sushi as a staple part of a
local restaurant scene, regardless of the local population’s background. The negative
coefficients for Mexican restaurants in several California counties (generally with
relatively large Mexican populations) may reflect a similar process, in which Mexican
restaurants now routinely exist in neighborhoods with relatively low (for that county)
proportions of Mexican residents. The large number of counties with negative
relationships for French restaurants may also be worthy of note. These are all counties
with relatively large French American populations in which their relative dearth of
French restaurants stands out all the more. A county like Atlantic, New Jersey, may be
more likely to have tourist-oriented neighborhoods with many Italian restaurants but few
Italian residents.
These results illustrate the diversity of ways in which ethnicity and amenities such as
restaurants may be integrated or separated, and they lay the ground for empirical
generalizations about the likelihood of various combinations occurring and further
examining their origins and impacts. However, the results for different groups are not
directly comparable. In the second phase of analysis, we therefore join the various groups
into a single model. We do this by treating each group as a repeated measure of the same
zip code. Thus, we have eleven measures of ancestry and restaurant proportions for each
zip code, which we can in turn probe further in a multilevel modeling context.

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Figure 1. The interaction of ancestry and
restaurants
Note: This figure summarizes key results from a
multi-level regression model, covering all US zip
codes. For each zip code there are eleven repeated
measures of a) ancestry and b) restaurants,
corresponding to the eleven ethnic groups
summarized in Table 4. Ancestry is the dependent
variable. The model includes as fixed effect
independent variables restaurants, ethnic groups,
and their interaction term. Zip code is the level 2
variable. The figure shows only results for the
interaction term. Larger coefficients mean that the
association between restaurant and ancestry is
stronger for that group, relative to the reference
category (French).
Figure 1 shows a first step in this direction, comparing the strength of ancestry–
restaurant associations across groups. The figure compares interactions between group
and restaurant concentrations. French ancestry is the reference category.
As Figure 1 shows, the
association between ethnic
restaurants and a
corresponding local
population is strongest for
Cubans and African
Americans, followed by
Irish. People from these
groups are the most likely
to live near “their”
restaurants, accounting for
the relative size and
concentrations. Chinese,
French (the reference
group), and Greek
Americans are the least
likely to live near “their”
restaurants. And while
Mexican, Italian, German,
and Korean Americans are
more likely than French to
live near “their”
restaurants, they are
substantially less likely to
do so than Cubans, African
Americans, and Irish
Americans. In many cases
this may indicate a broad
diffusion of a cuisine into American popular culture. For instance, one may find Chinese
restaurants where very few people of Chinese descent live, whereas to eat Cuban or soul
food (or Irish cuisine) one needs to go where Cuban and African American (and Irish)
people live (on Chinese restaurants in Canadian small towns, see Cho 2010). Mexican is
probably in between—diffusing more broadly, but nevertheless relatively strongly linked
with Mexican neighborhoods.
Next we examine how these associations shift across counties. This model includes the
fixed effect interaction from Figure 1, but it adds restaurant random effects for various
ethnicities nested in counties. Random effects thus take account of, for instance, the fact
that in general the African American–soul food association is relatively strong and
highlights counties in which the association is especially striking, taking also into

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consideration the concentration of a particular group in that city (which the county
intercept identifies).
Results are difficult to summarize succinctly. Table 5 illustrates by showing the top fifteen
associations, though we discuss others in the text. All those listed in the table are
statistically significant. While these results largely confirm the ones summarized in Table
4, their added value comes in allowing for direct comparisons, accounting for relative size
and local concentrations of groups, and their typical association with corresponding
restaurants. For example, the African American association with soul food restaurants in
Chicago is particularly dramatic. The Cuban ethnicity–restaurant association in Dade,
Florida, is similar to that of Mexicans in Santa Cruz, California, or Italians in Essex
(Newark), New Jersey, among others—again relative to their typical associations and
what would be expected based on local population concentration alone. Interestingly, the
Irish ancestry–restaurant association, while strong on average, does not seem to stand
out especially strongly in a given locale (Boston is the sharpest), whereas for Mexican
Americans it is weaker (than Irish) overall but stronger in many particular areas (such as
Kane, Illinois, in suburban Chicago or Adams, Washington, which by 2010 was nearly 60
percent Hispanic).
Table 5. Comparing the Restaurant/Ethnicity Overlap across Groups and Places
Ethnicity County County
Intercept
Restaurant Random Effect
on Ancestry
African
American
Cook, IL 0.15 0.21
African
American
Los Angeles,
CA
0.01 0.12
Mexican Kane, IL 0.04 0.10
Cuban Dade, FL 0.24 0.10
Mexican Santa Cruz,
CA
0.04 0.10
Mexican Adams, WA 0.07 0.09
Mexican Los Angeles,
CA
0.14 0.09
Italian Essex, NJ 0.09 0.09

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African
American
Erie, NY 0.03 0.09
Mexican Collier, FL 0.03 0.09
Mexican Maverick, TX 0.41 0.08
Italian Philadelphia,
PA
0.04 0.08
Mexican Elko, NV 0.09 0.08
Mexican Cook, IL 0.02 0.08
Note. This table shows the top fifteen counties where the association between
restaurants and local ethnic populations is strongest. These are random effects from a
multilevel model in which the ancestry–restaurant interaction is included as fixed
effect level 1 variables (as described in the note to Figure 1). Restaurants are also
included as random effects varying within ancestries nested in counties. Higher
coefficients mean that in that county the association between restaurants and ethnicity
is particularly strong, taking into account the typical relationship and local population
concentration.
The multilevel approach allows an additional analysis (not shown) of counties in which
the restaurant–ancestry association is relatively strong as such. These are counties where
independent of the particular group, ethnic restaurants and corresponding populations
tend to co-locate. Here, two counties stand out in particular: Cook, Illinois, and Los
Angeles, California. These are the only counties in which the relationship is statistically
significant.
Our third and final analysis examines characteristics of zip codes with cosmopolitan,
diverse arrays of restaurants. We measure restaurant diversity by computing a Rao-
Stirling index across fifty-three different types of restaurants. The Rao-Stirling index
combines three dimensions of diversity (Stirling 2007): variety, or the number of different
types of restaurants in a zip code; balance, or the evenness of the distribution of
restaurant types; and disparity, or how unusual the combination of restaurant types is.
High scoring zip codes include downtown Portland, the Boston Common area of Boston,
New Orleans’ Treme, Queens Village in New York, The Castro in San Francisco, and
Chicago’s Devon Avenue area. The index has strong face validity.
To investigate the character of these cosmopolitan restaurant scenes, our model includes
a range of standard urban variables, as well as four composite measures of scenes (see
Scenescapes ch. 5 for more detail), which capture key aspects of American scenes: (1)
urbanity, which joins corporateness, rationalism, and utilitarianism along with

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Figure 2. Characteristics of zip codes with
cosmopolitan restaurant scenes
Note: This figure shows neighborhood characteristics
associated with zip code restaurant diversity, based
on a multi-level regression model to examine the
Rao-Stirling cosmopolitanism restaurant index with
zip code as level 1 and county as level 2, covering all
US zip codes. These are fixed effect results. Racial
diversity is measured as an entropy index of 14 racial
categories, and change in racial diversity as the
difference between 2010 and 2000. Change in rent
and population is measured as the ratio of 2010 to
2000; levels of census variables are from 2000.
Unless otherwise indicated, all variables are at the
zip code level. All VIFs are approximately 3 or lower.
transgression, glamorousness, and self-expression, and has relatively high concentrations
of fast food, delis, lawyers, cafes, health clubs, commercial artists, and jewelers, and
relatively few churches; (2) LA LA Land, strong in glamour, exhibition, self-expression,
and transgression, with concentrations of night clubs, health clubs, and body piercing,
and relatively few campgrounds and truck stops; (3) Rossini’s Tour, which combines self-
expression with local authenticity in concentrations of items such as fishing lakes,
antique dealers, art galleries, book shops, and marinas, with few fast-food restaurants; (4)
City on a Hill, especially strong in egalitarianism but also tradition and neighborliness,
with relatively large concentrations of public libraries, churches, hospitals, and recycling
centers, and few yacht clubs, equestrian centers, and ski resorts.
Figure 2 shows aspects of
typical areas with highly
diverse restaurant scenes.
They tend to overlap with
urbane scenes and those
that feature
glamorousness, personal
expression, and
transgressiveness. Such
areas are simultaneously
highly educated and have
many young residents. But
they do not fit the
standard model of
gentrification: rather, the
scene is one of not only
greater racial diversity but
also of increasing racial
diversity and rising
education, plus the joint
effect of race times
education (captured in
separate rows of the
figure). These
cosmopolitan areas are
also generally in dense
parts of large, relatively
expensive cities, with many singles, relatively few baby boomers, and relatively high and
increasing concentrations of young people. These neighborhoods also show generally
strong population growth. In contrast to claims that globalization leads to culturally bland
homogeny, what this more micro- and mixed-level scenes analysis shows is more
neighborhood diversity, across many dimensions. Moreover, relative to other dense,
highly educated areas, cosmopolitan restaurant scenes have relatively low median rent,

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which is in turn growing at a relatively slow pace. They can thus appeal to creative but
underfunded chef/restaurant entrepreneurs, among other creative aspirants. In sum,
these diverse restaurant scenes are parts of dynamic and diverse neighborhoods, filled
with talented young people, which, even as they grow rapidly and become even more
diverse, manage to remain relatively affordable.
We thus end with a scene that is at the other end of the spectrum from the classic closed
ethnic neighborhood. Contrasting the latter with the openness and interpenetration of
multiple scenes dynamics in different neighborhoods of the same cities clarifies some of
their multiple yet interpenetrating dynamics.
Discussion and Conclusion
Taken together, the analyses herein provide interesting material to inform social research
into the interplay of ethnicity and consumer amenities. They confirm the proposition that
ethnically themed amenities and ethnic populations overlap in many ways, and that it is
possible to more systematically analyze the conditions in which various configurations
occur.
A number of more specific insights also emerge. For instance, our results confirm some
older propositions, for instance that Chicago remains distinctive in supporting strong
ethnic neighborhoods and that, even after centuries of “assimilation,” Irish Americans
retain a relatively strong attachment to their particular local institutions—whether this is
associated with a continuing “Irish Ethic and the Spirit of Patronage” (Clark 1975) is a
question worth pursuing further. By contrast, the fact that Los Angeles emerges as a
strong center of distinctive ethnic neighborhoods is especially intriguing. While
consistent with recent discussions of multicultural cities, it directly contradicts the
“placeless” image of Los Angeles promulgated by the Los Angeles School of Urbanism,
which for example tends to discuss Los Angeles and Orange counties as generically
“fragmented,” rarely invoking any specific ethnic group names (cf. Judd and Simpson
2011). Similarly, our comparative results add context to Portes’s insights about ethnic
enclaves, derived initially from Cuban neighborhoods in Miami, or ideas derived from
Boston (Gans 1982; Small 2004) and Philadelphia’s (Wherry 2011) classic ethnic
neighborhood patterns. These are extreme cases that may help to formulate an especially
clear theory that for the same reason might not generalize elsewhere, without some
modification (Yoon 2013).
Our analyses reveal particularly strong linkages between African Americans and
distinctive consumption spaces. This is another indication of the legacy of segregation.
The finding takes on added importance in the context of debates about residential
mobility. Decisions to move are not simply economic, about jobs, but also involve
potentially abandoning a set of local amenities that give a neighborhood meaning and
familiarity (Portes and Rumbaut 2006; Small and McDermott 2006). That African
American neighborhoods are especially strongly linked with soul food restaurants is only
a small part of this dynamic—churches, among other amenities, are crucial too—but they

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indicate the broader range of concerns that must be taken into account in considering
what makes “moving to opportunity” more or less attractive (Sampson 2012).
Finally, our analysis of areas with ethnically diverse restaurants showed the distinctive
potential of these neighborhoods. Key meeting points in contemporary “multicultural”
cities, they are the consumption side of Logan and Zhang’s (2010) “global
neighborhoods.” Not defined by one single group, they are rapidly growing cosmopolitan
sites of mixing and mingling, in which racially diverse and highly educated young people
are increasingly concentrated in funky and exciting scenes. And yet even as they do so,
they remain, all things considered, relatively affordable. In this way, they provide a sharp
counterpoint to typical gentrification narratives and illustrate the diversity of possible
trajectories for neighborhood development.
Combing the thick with the thin “descriptive” accounts can generate conceptual ferment
and bring comparative insights. The challenge of “big data” is not that it is big but that it
is different and comparative. We can use it to drill down to smaller units as well as to
locate them comparatively, thus potentially generating more conceptual insight, more
potential to join other kinds of information about distinct topics and locations—more than
if methods or city names or specific ethnic groups or types of leisure activity (from sports
to social media or cuisine) are the sole organizing focus. A richer consumption analysis
needs all of these—not by arguing or ignoring, but by selecting central specific ideas from
alternative studies and reassessing them systematically in new contexts with new
neighbors. We can thus codify as well as qualify past work.
The major thrust of this chapter is to elaborate the scenes perspective to join with related
consumption-oriented research and to extend scenes work to empirically contrast ethnic
with cosmopolitan restaurant scenes. Having shown the great potential of this approach
by starting with a largely descriptive analysis of the interplay of restaurants and local
populations, we start to elaborate the broader scenes of which they are apart. This
analysis calls for extension. For instance, one could zoom in on particular cities and
neighborhoods identified by this analysis for qualitative research, featuring both outliers
and typical cases. One could also dig deeper into both historical processes that give rise
to particular amenity/population configurations and their consequences for other key
urban processes, such as economic development, migration patterns, and local politics.
We thus invite others to challenge and explore the richer and more subtle meanings of
urban and consumption dynamics that can substantially enhance the level of much social
science and especially broader public discussion of these issues.
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Notes:
(1.) “You can’t imagine what it is to walk in the streets of Astoria and hear nothing but
Greek; it’s like being in Athens” (http://www.nytimes.com/1991/11/15/arts/astoriaa-greek-
isle-in-the-new-york-city-sea.html?pagewanted=all)
(2.) Extending the analysis to additional items such as Irish saloons would be an
intriguing future direction, especially in light of Depuis (1999).
Daniel Silver
Daniel Silver, University of Toronto
Terry Nichols Clark
Terry Nichols Clark, University of Chicago