Scenes, Nonprofits & Urban Development

Presentation forUAA 2009New Roles for Urban Nonprofits

Terry Nichols Clark&Eric Allix Rogers University of Chicago

scenes.uchicago.edu

Nonprofits in CitiesNonprofits are a key component of city infrastructureLink public goals with public and private resourcesBuild networks of engaged constituentsAddress needs and opportunities creatively and flexibly Strengths can also be liabilitiesFlexibility often means unreliable fundingNetworks are more often than not geography-basedCreative solutions are also place- and time-specific

Entrepreneurialism is InThe opportunities and challenges facing nonprofits are very similar to those of small businesses. Not coincidentally, the organizations and practices in the NPO field are becoming much more entrepreneurial. Membership and fee-for-service revenue modelsIncreased attention to performance & metrics Blurring the distinction between for-profit and nonMany consulting firms focus on NPOsBusinesses with a social vision

Experimental StationIndustrial building on South Side, renovated to be extremely environmentally sustainable.

Blackstone Bicycle WorksRefurbishes and sells used bikesFunds after-school program for neighborhood students at shop

Backstory CafFor-profit, rents spaceStages a wide range of community eventsAims to serve as an infoshop

Agriculture/food programsNearly year-round farmers market, which accepts LINK (food aid) cardsCommunity garden Event/cultural space

North Lawndale Employment NetworkEmployment training and assistance agency on West Side, focusing on released prisoners.

Case-by-case assistance for job seekers, particularly those who have been in prison. Computer literacy and skills training Sweet BeginningsTransitional employment program for formerly incarcerated individualsA for-profit subsidiary of NLENKeeps bees in parks and vacant spaces in the community, creates personal care products from honey and beeswax

Co-Prosperity Sphere/Public Media Inst.Large former store on the South Side, converted into a multi-use cultural space.Performances and cultural eventsGallery spaceActivist meeting and conference space

Public Media InstituteArts and design publicationsAnnual alternative arts and media festivals

Artist residency program

Diversity of Churches

Context MattersThese organizations all respond creatively to the needs and opportunities presented by their communities. They blend traditional nonprofit activities and funding sources with innovative, entrepreneurial, and deeply place-dependent strategies for success. None of these organizations could be uprooted and moved to the site of another with any expectation of success.

Seeking AbstractionCase studies are valuable and interesting, but that knowledge is difficult to abstract and apply.

Simple quantitative approaches that focus solely on traditional indicators miss the nuance of diverse communities.

Is there a third way?

Scenes: An Analytical AlternativeCapture and summarize a large amount of subtle variation between places.

Draw on the vast amount of data that exists in silos that are not ordinarily connected.

Simultaneously embrace the cultural turn in sociology while allowing the use of sophisticated new quantitative analytical techniques.

A Multi-Level Research ProgramBackgroundSocial and Cultural Change: rise of consumption & cultureGlobalMulti-Disciplinary Theoretical LevelBasic assumptions (action, consumption, meaning, interaction)Conceptual analysis (bring phenomenon into view)Model-building (analytical elements) Methodological LevelOperationalization Empirical LevelExamples & Exploratory Propositions

Cultural Participation Generally Rising

World Values Survey, US and Dutch citizens show dramatic rise in cultural participation, tripling in the US in 18 years; but not in France. Bigger rise than for other forms of participation.(US N= 3525 citizens, national sample)

Embracing cultural heritage and public spacePiazza del Plebiscito, Naples

Beautification (and emulation)

Civicness & Public Spaces in Bogota

Theoretical Background

Invoked by critics as loose collection of people and activities involving cultureBlues in Chicago, Theater in New York More than amenities or arts per seThe beach scene in MiamiBeach, but also chance to ogle and be ogled, bars, music, restaurants, hedonism.Neighborhood scenes: Wicker Park, Haight-Ashbury, SoHo Linked with broader themes in cultural studiesDynamic Village in The City (Straw, Blum)Product of modernization, individualization, consumer society (Irwin)Graft tastes and affinities to physical locations, unify seemingly heterogeneous activities, provide grooves for cultural reproduction of urban sociality (Straw)Aesthetic criteria are joined to scene dimensions

Components of a Scene1. Neighborhood (area) 2. physical structures and spaces 3. persons labeled by race, class, gender, education, etc. 4. the specific combinations of the above 3 and activities (like attending a concert) which join them. These four components are in turn defined by 5. the values people pursue in a scene. General values are legitimacy, defining a right or wrong way to live; theatricality, a way of seeing and being seen by others; and authenticity, as a meaningful sense of identity.

Scenes as Systems of Social ConsumptionParsons on social action; Scenes as specific form of social actionConsumer vs. Worker vs. Resident

SpaceSceneNeighborhoodIndustrial-DistrictGoalExperiencesNecessitiesWorks, productsAgentConsumerResidentProducerPhysical UnitsAmenityHome/ApartmentFactoryBasis of social bondValuesbirth, local residence, ethnicity, heritageWork / production relations

Urban Amenities Data SourcesUS Census of BusinessYellow PagesDDB Lifestyle Surveys (n=84,000)Dun & Bradstreet arts organizationsUrban Institute Unified Database of Arts Organizations (UDAO)IRS 501c3 reportsOther industry & governmental datasets

Urban Amenities DatabaseNational: covers all US cities, nearly 40k zip codes for some variablesUnifiedIncludes other standard variables (Census, schools, crime, etc.)Open-ended and scalableData is regularly addedSimilar approaches can be used elsewhere (Canada)

CONCEPT

DIMENSIONS

SUBDIMENSIONS

Specific Scene = empirically discovered correlation or theoretically defined linkage among sub-dimensions. Example: sub-dimensions in red are important elements of a bohemian scene.

SCENE

Spatially Organized Social Consumption Activity

AUTHENTICITY: IDENTITY, SELF-REALIZATION

THEATRICALITY:APPEARANCE, MUTUAL SELF-DISPLAY

LEGITIMACY:

INTENTIONS, REASONS FOR ACTION

T

R

A

D

I

T

I

O

N

A

L

I

S

M

RAT

IONAL

--

CORPORATE

--

STATE

ETHNIC

LOCAL

FORMAL

G

L

A

M

O

U

R

EXH

I

BI

T

I

ONI

SM

TRANSGRESS

I

ON

NE

I

GHBORL

I

NESS

EGAL

I

TARIANI

SM

UT

I

L

I

TARIANI

S

M

CHARI

SMA

SELF

-

EXPRESS

ION

Three dimensions of cultural valueTheatricality. As the very word scene implies, one thing that may be sought in a cultural experience is the chance to see and be seen. Participants seek the essentially social pleasure of performing a role or a part, or of watching others do so.Authenticity. Cultural experiences, even theatrical experiences, may aim to provide a sense of an authentic cultural tradition, activity, or identity. Legitimacy. Cultural experiences may be intended to encourage a sense of what is right and wrong, how one ought to live.

Theatricality or the Pleasure of Seeing and Being SeenStanding on the red carpet at Cannes ogling the stars going by. Going to the opera in white tie and tails. Watching a performance artist pierce his skin. Sharing the experience of a school play with other parents. Jumping onto a raised platform to dance in front of a crowd at a rave.

The value of displaying charm, allure, star power, and statusVersus exhibitionism, where value is in being object of gaze (woman in window need not be glamorous)Designer boutiques, night clubs with VIP rooms, Prada and Gucci storesPro: movie openings, design schools, TV and movie production, art galleries, interior design firms, beauty salons, advertising firms, fine art dealers/galleries, department stores, opera companies, private golf clubs, fine dining restaurants, designer clothing, custom jewelry storesAnti: warehouse stores, convenience stores, NASCAR tracks, scientific R & D, bowling centers, convents/monasteries, country music clubs, bible stores. Theatricality: Glamour

The value of closeness, personal networks, and intimacy of face-to-face interactions

Amenities affirm sense of being part of a warm, inviting community (Little League, reading clubs)

Value lies in interaction vs. authenticity

Pro: community centers, street fairs, pubs, bowling alleys, bed and breakfast inns, religious organizations, community organizations, business organizations, bakeries, florists, county fairs and festivals, sports clubs

Anti: warehouse clubs and superstores, department stores, amusement parks, fast-food restaurants, tele-communication networks

Theatricality: Neighborliness

The value of feeling rooted in a place

Pro: Local restaurants, farmers markets, community theatre, independent bookstores, independent music stores, historical sites, bed and breakfast inns, spectator sports, souvenir stores, antiques and collectibles, film festivals, county fairs and festivals

Anti: Warehouse clubs and superstores, human rights organizations, casinos, computer systems, design, and related services, convenience stores, fast food

Authenticity: Locality

The value of unique, personal expression

Pro: fashion houses and designers; body piercing; custom printed t-shirts; jazz clubs; modern dance; experimental music & theatre; Dance companies; Fine arts schools; art dealers; Musical groups & artists; Independent artists, writers & performers; Graphic design services; custom computer programming services; interior design; comedy clubs; arts & crafts classes

Anti: business and secretarial schools; business associations; offices of lawyers; scientific research centers; database and directory publishers; Catholic churches; folk arts; industrial designLegitimacy: Self-Expression

Legitimacy: EgalitarianismThe value of universal equality, treating others non-strategically, as ends-in-themselves

Pro: human rights orgs; junior colleges; Christian churches; social advocacy organizations; public schools; community service orgs (YMCA); salvation army; public aquariums; public tennis courts; public festivals; public libraries; free public lectures

Anti: private golf and tennis clubs; casinos; private clubs; yacht clubs; gourmet restaurants; equestrian; cigar bars

Legitimacy: CharismaThe value of being in the presence of an exceptional personality.

Jesse Owens vs. Chicago Marathon; Blockbuster shows or concerts; Public art by famous artists

Pro: spectator sports; motion picture theaters; Film festivals; performing arts; book stores; public relations agencies; television broadcasting; political orgs; fashion; designer clothing and accessories; art galleries; government: executive; popular music;

Anti: scientific R & D; wilderness refuge and nature preserves; fast food restaurants; salvation army; industrial design; physical sciences research centers; big band

15 SubdimensionsThere are a total of 15 subdimensions that, altogether, allow us to evaluate much of what makes different scenes unique. The subdimensions are theoretically grounded, but also make intuitive sense. For more information on the concept, see A Theory of Scenes (available online at scenes.uchicago.edu)

From Concept to Operational Tool: Coding Values1. Create an index of standards of value.5-point scale:(5) Essential: expressivity for experimental music, traditionalism for heritage sites, glamor for couture shows(4) Desirable, but not determinative alone: traditionalism in used and rare bookstores(3) Neutral: not positively or negatively shaping the experience of the amenity(2) Undesirable but not a deal-breaker: utility for interior design firms(1) Antithetical: amenity contrary to value, i.e., egalitarianism and country clubs

2. Code each category of amenity for all sub-Dimensions

AmenityEthnic authenticityCorporate authenticityTransgressive TheatricalityGospel Singing Groups422Poetry Slam Venues424

3. Generate scene profile for zip codes, etc.

Primary Measure = Performance Score (Average score per amenity for each dimension in each zip code) Other measures: Manichean, Cultural Diversity Index, Factor Analysis, Bliss Points

Sheet1

Bizzip

BizzipTraditionalistic performanceSelf-Expressive performanceUtilitarian performanceCharismatic performanceEgalitarian performanceNeighborly performanceFormality performanceExhibitionism performanceGlamorous performanceTransgressive performanceRational performanceLocality performanceState performanceCorporateness performanceEthnicity performance

National Average3.0663.03172.73043.16853.19313.19773.14233.13333.06862.70422.96023.04672.7872.9992.9877

10016 NY, New York3.013.122.953.183.013.033.323.093.142.793.012.932.983.232.98

10017 NY, New York3.013.092.943.193.023.043.43.073.122.773.032.912.973.212.98

10018 NY, New York3.033.232.883.23.023.023.23.083.122.792.982.942.983.192.98

60647 IL, Chicago3.033.112.843.143.083.063.123.113.062.812.992.992.953.062.99

60622 IL, Chicago3.043.222.833.23.053.043.153.113.132.742.962.982.963.22.98

90027 CA, Los Angeles3.033.262.783.263.063.053.063.143.152.872.922.972.912.962.99

90028 CA, Los Angeles3.033.262.843.273.053.033.113.093.152.872.932.942.953.152.99

YP

Yellow PagesTraditionalistic performanceSelf-Expressive performanceUtilitarian performanceCharismatic performanceEgalitarian performanceNeighborly performanceFormality performanceExhibitionism performanceGlamorous performanceTransgressive performanceRational performanceLocality performanceState performanceCorporateness performanceEthnicity performance

National Average3.28112.96522.44733.23033.22473.23113.20962.96872.66252.38082.47582.96722.70092.66662.9276

10016 NY, NEW YORK2.983.032.553.062.82.82.9132.842.512.592.842.762.82.92

10017 NY, NEW YORK3.063.152.73.172.962.983.033.082.972.82.832.962.932.963.07

10018 NY, NEW YORK2.813.282.413.412.652.753.113.283.212.522.472.782.762.952.83

60647 IL, CHICAGO3.112.922.543.12.982.973.022.882.72.462.462.82.672.72.9

60622 IL, CHICAGO3.093.032.583.142.892.892.983.022.822.582.492.872.782.822.97

90027 CA, LOS ANGELES3.042.962.453.082.872.862.942.952.722.472.412.772.662.712.87

90028 CA, LOS ANGELES2.833.022.363.052.692.712.783.12.842.672.452.752.692.742.79

Sheet2

Traditionalistic performance

Self-Expressive performance

Utilitarian performance

Charismatic performance

Egalitarian performance

Neighborly performance

Formality performance

Exhibitionism performance

Glamorous performance

Transgressive performance

Rational performance

Locality performance

State performance

Corporateness performance

Ethnicity performance

Sheet3

Descriptive Statistics

Mean

Traditionalistic performance3.066

Self-Expressive performance3.0317

Utilitarian performance2.7304

Charismatic performance3.1685

Egalitarian performance3.1931

Neighborly performance3.1977

Formality performance3.1423

Exhibitionism performance3.1333

Glamorous performance3.0686

Transgressive performance2.7042

Rational performance2.9602

Locality performance3.0467

State performance2.787

Corporateness performance2.999

Ethnicity performance2.9877

trad YP3.2811

se YP2.9652

ui YP2.4473

char YP3.2303

egal YP3.2247

neigh YP3.2311

form YP3.2096

exhi YP2.9687

glam YP2.6625

trans YP2.3808

rat YP2.4758

loc YP2.9672

sta YP2.7009

corp YP2.6666

eth YP2.9276

Regional Variation in ScenesMidwest and South are more traditionalistic; Northeast and West value individualSelf-expression most; Western scenes are both transgressive and corporate;Midwest is most neighborly and exhibitionistic.

Chart1

-0.0820.082-0.0370.114

0.083-0.1450.117-0.051

-0.0990.118-0.080.01

-0.0340.111-0.1020.047

0.009-0.0660.1220.064

South

West

Midwest

Northeast

Pearson Correlations

Sheet1

Correlations

SouthWestMidwestNortheast

Pearson CorrelationTraditionalistic0.071-0.0820.0960.01

Self-Expressive-0.0820.082-0.0370.114

Utilitarian0.0030.066-0.141-0.003

Charismatic0.074-0.0830.0550.012

Egalitarian0.102-0.1160.091-0.054

Neighborly0.083-0.1450.117-0.051

Formality0.003-0.046-0.012-0.014

Exhibitionism0.009-0.0660.1220.064

Glamorous-0.012-0.0440.0320

Transgressive-0.0990.118-0.080.01

Rational-0.0870.063-0.1190.04

Locality-0.041-0.0010.0830.05

State-0.1150.123-0.1030.074

Corporateness-0.0340.111-0.1020.047

Ethnicity0.042-0.040.079-0.008

SouthWestMidwestNortheast

Traditionalistic0.071-0.0820.0960.01

Self-Expressive-0.0820.082-0.0370.114

Neighborly0.083-0.1450.117-0.051

Transgressive-0.0990.118-0.080.01

Corporateness-0.0340.111-0.1020.047

Correlations

TraditionalisticSelf-ExpressiveUtilitarianCharismaticEgalitarianNeighborlyFormalityExhibitionismGlamorousTransgressiveRationalLocalityStateCorporatenessEthnicity

Pearson CorrelationSouth0.071-0.0820.0030.0740.1020.0830.0030.009-0.012-0.099-0.087-0.041-0.115-0.0340.042

West-0.0820.0820.066-0.083-0.116-0.145-0.046-0.066-0.0440.1180.063-0.0010.1230.111-0.04

Midwest0.096-0.037-0.1410.0550.0910.117-0.0120.1220.032-0.08-0.1190.083-0.103-0.1020.079

Northeast0.010.114-0.0030.012-0.054-0.051-0.0140.06400.010.040.050.0740.047-0.008

TraditionalisticSelf-ExpressiveNeighborlyTransgressiveCorporatenessExhibitionism

South0.071-0.0820.083-0.099-0.0340.009

West-0.0820.082-0.1450.1180.111-0.066

Midwest0.096-0.0370.117-0.08-0.1020.122

Northeast0.010.114-0.0510.010.0470.064

Sheet1

South

West

Midwest

Northeast

Pearson Correlations

Sheet2

Sheet3

Metropolitan Variation in ScenesMetro averages on Scenes dimensions: LA leads on self expression; Chicago is most neighborly; New York most utilitarian; ; all exhibit similar mega-city pattern

0 = US national average; NYC, LA and Chicago are county averages from zip codes

Metropolitan Variation in Scenes, contd.L.A. most glamorous and transgressive, NYC mixes transgression, rationalism, statism and corporateness0 = US national average; NYC, LA and Chicago are county averages from zip codes

Correlations: Scenes and NGOsCOMMENTCorrelations from Census of Economics 2001 performance scores, standardized. Org. info from same source. Sign reversed for ease of interpretation.

Scenes as interrelations between kinds of valueHow to define interrelations? A posteriori A priori A posteriori: factor analysis and correlationsNational-Level Factor analysis (of zips and counties) shows some value-dimensions are strongly linkedCorrelations among scene dimensions vary, among cities, regions, and other units of analysis.

Scenes Factor AnalysisScenes dimensions cluster by factors in intuitive ways.Clusters hold together across data sources.

Metro Level CorrelationsCharisma in Chicago is correlated with local authenticity, neighborlyTheatricality, and egalitarian legitimacy. Chicago is a city where charisma is channeled into the local scene, the city of neighborhoods. Charisma in NYC and LA is linked with individual self-expression and glamour.

Metro Level CorrelationsMore than in L.A. and NY, scenes in Chicago link self-expressive individualism with utilitarian legitimacy, rational authenticity, local authenticity, and corporate authenticity.Self-expression in Chicago scenes is more weakly tied to charismatic legitimacy, glamorous theatricality,and transgressive theatricality than in L.A. and N.Y. scenes.

A priori approaches to scenesScenes can be defined as ideal-typical combinations of dimensions in several ways.

Proximity to bliss points: Bohemia, Disney Heaven, Bobo, Rossinis Tour, etc.

Degree of ecumenicism. Scenes may encourage an openness to all things human, offering many different kinds of experiences, involving many kinds of value.

Cultural difference/diversity. Scenes may encourage an openness to conflicting values and internal tensions across a number of dimensions.

Flow. Scenes may encourage a letting-go or loosening of norms.

Work. A scene may promote efficient, disciplined activity directed toward a corporate end.

BohemiaConcept has become central in theories of consumption, amenity-drivenurban growth, and post-industrial society (Campbell, Clark, Florida, Lloyd).

It is possible to operationally define a Bohemian scene in terms of how close empirical scenes come to an ideal-typical Bohemian profile.

The 30 most Bohemian zip codes in Chicago areSource for neighborhood-zipcode crosswalk: Chicago ReaderNote: lower score = more Bohemian

Social and Demographic Factors Associated with BohemiaBohemias are more prevalent in parts of the country with higher population, more retirees (Gray creative class), higher rents, less education (level), more crime (cf. Lloyd), increasing college grads, and fewer non-whites. Politics, income, baby boomers, and youth not significant. Change in retirees, youth, and baby boomers not significant.

What do Scenes Do?Economic impact: jobs, property values, incomeSocial impact: demographic change, crime, community indicatorsPolitical impact: civic engagement, voting, political affiliation

Analytical OptionsAdd scenes measures to traditional set of factors in urban development models (safety, schools, crime, etc.)Compare zip codes, cities, and regions with similar scenes to show how a given type of scene interacts with other variables.

Application: Impact of Scenes on Migration PatternsCohorts of interest: nonwhites, retirees, 18-24 year olds, 25-34 year olds, baby boomers (in their 40s and 50s), college graduates, and college graduates combined with graduates of graduate and professional schools How strong a factor is the scene in a zip code in accounting for changes in the % of college grads (or other cohorts) moving there?Related question: do college grads in different cities flow toward the same kinds of scenes?

Standard Independent VariablesZip code variables:per capita income proportion non-white population County level variablespopulation size rent (as a measure of both the local housing market and cost of living)percent Democratic voting in the 1992 Presidential election

Example: What scenes attract or repel different demographic groups?Dependent variables are change in share of population for: 18-24; 25-34; baby boomers; retirees; college grads; non-whites

Example: What attracts the creative class?

Scenes affect migration by demographic groupsNationally, different subgroups increase their numbers in different types of scenes. Young adults increase in glamorous areasBaby boomers avoid glamour but link to Christian ChurchesCollege and professional graduates avoid egalitarian amenities, while non-whites seek them.Results hold strong in OLS multiple regressions and HLM models.

From National to Contextual: Variations in MigrationMany city-level and individual-level variations are not captured in national regressions with all zipcodes.Demographic groups may migrate differently in different cities.Bohemia attracts college grads in Chicago, not LA or NYWithin the settings of different scenes, effects of some values may be heightened or weakenedIn the more traditionalistic half of the country, glamour explains college grad increase more powerfully than self-expression does (nationally, relationship is reversed).

College grads flow to Bohemia in Chicago, not L.A. and N.Y.

Example: Modeling NGOsWe can improve simple models of NGO type distribution by using Scenes measures. Our standard model includes population, race, rent, presidential party voting, education level, crime rates, and arts jobs.Linear regression with these independent variables, with the presence of several types of NGOs as the dependent variables.Then, for continuity, well add the bohemian bliss point measure.

Criteria for success:Overall improvement to the models variance explainedSignificant, interpretable relationship between the scene measure and the outcome variable.

NGOs: More variance explained

Average R2, standard model0.132Average R2, with bohemia added0.193Average percent increase in R250%

NGOs: A more interesting modelIn all models, the bohemia measure had a significant and interpretable coefficient.

Implications & OpportunitiesBreak up simple urban growth/development concepts.Add specifics to fiscal, human, and social capital to help focus and target planning, for municipalities or organizations.Add policy specifics to power, regime, and political leadership.Identify dynamics of distinct scenes (bohemia vs. NASCAR scenes, etc.), and figure out how to augment them appropriately.Identify scenes with neighborhoods.

********************Amenities will make patrons feel as if they are at the center of the world of fashion. Dress codes to exclude the uncool.*Webers Gemeinschaft, associated by Tonnies with traditional bonds of locality, kinship, and family. But those bonds are values in themselves, in different dimension of authenticity, and they offer authority as well. ********These are sample performance scores from Bizzip and YP. Zips are: lower east side/downtown manhattan, wicker park/bucktown, hollywood. Note differences between national averages from two sources. Problem: magnitude of performance doesnt capture all features of a single valueIn relation to a single value, a neighborhood or city may bePurist: amenities either encourage or discourage the value churches discouraging transgression but no liquor stores encouraging transgression;ORManichean: liquor stores and churches co-existing in same neighborhood

*Compare this now to earlier slides that showed which zips have more cafes or theaters -- say how this tells us much more than the previous one, which was atomistic and positivisitic. Introduce idea of exhibitionism and glamour as sometimes linked with tradition, glory, status -- like conspicuous consumption*See file metro scenes for pp for source data. *See file metro scenes for pp for source data. *Comment: NGOs in general tend to follow similar patterns with respect to scenes, but notice in particular that religious and civic/social are very different. We can run simple correlations like this with ANYTHING, to see how it relates to our scenes dimensions, and do much more sophisticated things as well.*****Proximity to bliss pointsIndicator: an ideal Bohemian or Cosmopolitan or Disney Heaven, etc. scene

Degree of ecumenicism. Scenes may encourage an openness to all things human, offering many different kinds of experiences, involving many kinds of value. Indicator: the mean performance score for all 15 dimensions.

Cultural difference. Scenes may encourage an openness to conflicting values and internal tensions across a number of dimensions.Indicator: average coefficient of variation across all dimensions.

Flow. Scenes may encourage a letting-go or loosening of norms.Indicator: self-expressive legitimacy plus transgressive theatricalcity minus traditional legitimacy minus formal theatricality

Work. A scene may promote efficient, disciplined activity directed toward a corporate end. Indicator: utilitarian legitimacy plus corporate authenticity plus rational authenticity.

********The 25-34 year old age cohort has been widely discussed. In recent years it is often considered the core of Richard Floridas creative class. Our regressions show that 25-34 year olds increased in numbers from 1990 to 2000 in zipcodes with higher scores on utilitarianism, glamour, neighborliness, proportion nonwhites, larger populations, lower rent, and more Democratic voters. They avoid zip code areas with more traditional scenes and Christian churches. Self-expression is insignificant. (We sometimes use active language like avoid although clearly recognize the qualifications on causality and that these are ecological-level relations, not for individuals.). These results are broadly consistent with other portraits of preferences of this young adult age group. Still, we caution that the adjusted R2 is only .02, which is medium high (compared to the other subgroups we consider). That is many city-level and individual-level variations are not captured in the national regressions which combine all US zipcodes. City-specific differences are in the graphics. Many other factors operate to shift migration besides those in our models, but the overall explanatory power (R2) of these results is broadly similar to those in similar studies.

College grads: In contrast to 25-34 yr olds, college grads are attracted not to glitz and glamour but to individual self-expression and aMore neighborly scene, they avoid egalitarian scenes, and rise where income is higher, there are fewer non-whites, and rents are higher. Politics Is relatively insignificant.

Nonwhites share some patterns with the 25-34 year olds: they increase in zip code areas that are more utilitarian and glamorous, but differ in choosing the more egalitarian (in contrast to college grads) and avoiding the more neighborly scenes. They also rise in zipcodes with lower per capita income, albeit in counties with higher rents and larger populations. They also grow in counties with fewer Christian churches (but with more Baptist and Pentecostal churches, not shown), and more Democratic voters. Whereas individual self-expression was not a significant factor for 25-34 yr olds, non-whitesAvoid individual expression, preferring glamour.

Retirees increase more in zip codes with less utilitarian and neighborly scenes, but glamour is insignificant. Indeed even non-significant patterns of this sortglamour is insignificant for retireestake on interpretive meaning when they contrast with results for other subgroups. Retirees increase more in areas with higher income, less population, higher rent, and fewer Democratic voters (at least for Bill Clinton in 1992).

Prof/Grad school grads are best explained (highest r2, with Baby Boomers after that. This suggests that the overall power of the models varies across subgroups in ways that make sense: 18 to 24 year olds are least well explained by these 11 factors. They are often living with their parents or unable to pursue their preferences as they are often still in school or working part time. Baby Boomers locations are best explained by the 11 variables, as they have income, are more stable and able to move to locations more consistent with their preferences and lifestyles. The other subgroups fall between these two on the adjusted R2s.) Prof/Grad Grads are square: attracted to utilitarian scenes, egal scenes

We do not comment in detail on every finding of this sort, but note a few more general patterns:

*We find strong and clear support for our basic hypothesis: different subgroups increase their numbers in different types of scenes. Thus young adults increase in glamorous areas, baby boomers avoid glamour but link to Christian Churches. College and professional graduates avoid egalitarian amenities, while non-whites are the opposite, and so forth.

*These scenes do not seem to be spurious. Results hold strong in OLS multiple regressions and HLM models including classic measures from related past work on migration and urban studies. *There have been many debates and mixed past results about the importance of amenities, culture, and scene-like factors in urban research and migration (e.g. Glaeser 2006; Kotkin misc; Cortwright). But many discussions have been based on few or weak data. The power of the scenes results may derive from our more extensive assembly of indicators than in any past work we have found on urban amenities. The most serious work has been by economists, who tend to focus on a small number of indicators each considered in isolation. See the review in Zelenev 2003?

*The overall power of the models varies across subgroups in ways that make sense: 18 to 24 year olds are least well explained by these 11 factors. They are often living with their parents or unable to pursue their preferences as they are often still in school or working part time. Baby Boomers locations are best explained by the 11 variables, as they have income, are more stable and able to move to locations more consistent with their preferences and lifestyles. The other subgroups fall between these two on the adjusted R2s.

*The 25-34 year old age cohort has been widely discussed. In recent years it is often considered the core of Richard Floridas creative class. Our regressions show that 25-34 year olds increased in numbers from 1990 to 2000 in zipcodes with higher scores on utilitarianism, glamour, neighborliness, proportion nonwhites, larger populations, lower rent, and more Democratic voters. They avoid zip code areas with more traditional scenes and Christian churches. Self-expression is insignificant. (We sometimes use active language like avoid although clearly recognize the qualifications on causality and that these are ecological-level relations, not for individuals.). These results are broadly consistent with other portraits of preferences of this young adult age group. Still, we caution that the adjusted R2 is only .02, which is medium high (compared to the other subgroups we consider). That is many city-level and individual-level variations are not captured in the national regressions which combine all US zipcodes. City-specific differences are in the graphics. Many other factors operate to shift migration besides those in our models, but the overall explanatory power (R2) of these results is broadly similar to those in similar studies.

College grads: In contrast to 25-34 yr olds, college grads are attracted not to glitz and glamour but to individual self-expression and aMore neighborly scene, they avoid egalitarian scenes, and rise where income is higher, there are fewer non-whites, and rents are higher. Politics Is relatively insignificant.

Nonwhites share some patterns with the 25-34 year olds: they increase in zip code areas that are more utilitarian and glamorous, but differ in choosing the more egalitarian (in contrast to college grads) and avoiding the more neighborly scenes. They also rise in zipcodes with lower per capita income, albeit in counties with higher rents and larger populations. They also grow in counties with fewer Christian churches (but with more Baptist and Pentecostal churches, not shown), and more Democratic voters. Whereas individual self-expression was not a significant factor for 25-34 yr olds, non-whitesAvoid individual expression, preferring glamour.

Retirees increase more in zip codes with less utilitarian and neighborly scenes, but glamour is insignificant. Indeed even non-significant patterns of this sortglamour is insignificant for retireestake on interpretive meaning when they contrast with results for other subgroups. Retirees increase more in areas with higher income, less population, higher rent, and fewer Democratic voters (at least for Bill Clinton in 1992).

Prof/Grad school grads are best explained (highest r2, with Baby Boomers after that. This suggests that the overall power of the models varies across subgroups in ways that make sense: 18 to 24 year olds are least well explained by these 11 factors. They are often living with their parents or unable to pursue their preferences as they are often still in school or working part time. Baby Boomers locations are best explained by the 11 variables, as they have income, are more stable and able to move to locations more consistent with their preferences and lifestyles. The other subgroups fall between these two on the adjusted R2s.) Prof/Grad Grads are square: attracted to utilitarian scenes, egal scenes

We do not comment in detail on every finding of this sort, but note a few more general patterns:

*We find strong and clear support for our basic hypothesis: different subgroups increase their numbers in different types of scenes. Thus young adults increase in glamorous areas, baby boomers avoid glamour but link to Christian Churches. College and professional graduates avoid egalitarian amenities, while non-whites are the opposite, and so forth.

*These scenes do not seem to be spurious. Results hold strong in OLS multiple regressions and HLM models including classic measures from related past work on migration and urban studies. *There have been many debates and mixed past results about the importance of amenities, culture, and scene-like factors in urban research and migration (e.g. Glaeser 2006; Kotkin misc; Cortwright). But many discussions have been based on few or weak data. The power of the scenes results may derive from our more extensive assembly of indicators than in any past work we have found on urban amenities. The most serious work has been by economists, who tend to focus on a small number of indicators each considered in isolation. See the review in Zelenev 2003?

*The overall power of the models varies across subgroups in ways that make sense: 18 to 24 year olds are least well explained by these 11 factors. They are often living with their parents or unable to pursue their preferences as they are often still in school or working part time. Baby Boomers locations are best explained by the 11 variables, as they have income, are more stable and able to move to locations more consistent with their preferences and lifestyles. The other subgroups fall between these two on the adjusted R2s.

*******