Abstract
Rising inequality and pro-affluent housing policy have led affluent Americans to become increasingly isolated into neighborhoods that only they are able to afford. I use an under-utilized and unusually large dataset to measure the effects of this isolation on affluent Americans’ perception of social conditions, including crime, healthcare accessibility, joblessness, and public school quality. I find that the affluent form perceptions of such social conditions by extrapolating from the conditions that exist in their own neighborhoods. When these neighborhoods are predominately affluent, offering little hint of the problems faced by the lower classes, the affluent take on perceptions of social conditions that are significantly more positive than the perceptions of everyone else in society. By leading politically and economically powerful affluent Americans to develop the false sense that others’ lives are as problem-free as their own, class isolation may imperil the prospects for improving social conditions in the United States.
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Notes
In addition to Oliver (1999, 2001), others have examined the effects of suburban living on political behavior (e.g., Gainsborough 2001). Yet it is important not to directly equate suburbanization with class isolation. It is now the case that more of America’s poor live in the suburbs than in inner cities, which was not true as recently as 2000 (Kneebone and Berube 2013). As a consequence, affluent Americans may live in suburbs and still live in close proximity to those of lower socioeconomic status.
Though Cruces et al. (2013) attribute people’s tendency to extrapolate from neighborhood conditions to the representativeness heuristic, other heuristics may contribute to this tendency as well. For example, the availability heuristic, which involves canvassing memory for relevant examples, may lead people to extrapolate from neighborhood conditions to form perceptions of social conditions if neighborhood conditions are foremost in their memory (Tversky and Kahneman 1973).
Due to an error in survey administration, an incomplete version of the survey that does not contain the necessary variables was administered to an additional 4880 respondents in 2010. Though these respondents are present in the publicly available data, I exclude them here.
No other variable is missing for more than 4 % of respondents.
While this subgroup analysis reflects the limits of a small sample size, it also provides suggestive evidence of substantively important effects. Specifically, there is preliminary evidence to suggest that class isolation may negatively affect affluent blacks’ participation in community-based efforts to address harmful social conditions. More research with a larger sample of affluent blacks is needed to test this potential finding, but if it were to hold, it would have important implications for black politics. Cooperation between affluent and non-affluent blacks to address harmful social conditions is part of the foundation of black political life (Dawson 1994), yet it may be imperiled should class isolation continue to rise. See Supplementary material Appendix p. 12 for more details.
The number of affluent respondents from other minority groups in the data, such as affluent Asians and affluent Latinos, is even fewer than the number of affluent blacks, preventing subgroup analyses of these other groups.
Throughout the text I use the term “metropolitan community” to reference the communities defined by the Knight Foundation and Gallup for the survey (see Supplementary material Appendix Table A1).
Full details on question wordings, coding, and distributions are available in the Supplementary material Appendix for all variables used in the analysis (p. 3).
The crime item question is as follows: “On a five-point rating scale, where 5 means extremely low and 1 means extremely high, how would you rate the level of crime in your community?”
1 on the original scale is converted to 0 on the new scale, 2 is converted to 25, 3 is converted to 50, 4 is converted to 75, and 5 is converted to 100.
This information was learned through extensive conversations with the director of the survey.
Notably, this measure compares the affluent’s perceptions to the perceptions of the non-affluent, rather than to objective reality itself. This aligns with H2, which concerns the positivity of the affluent’s perceptions relative to everyone else in society, rather than the accuracy of the affluent’s perceptions per se. While it is not the focus of this paper, objective reality—the aggregate experience of all members of a metropolitan community—is likely to lie in between the perceptions of the affluent and non-affluent. As the non-affluent are typically more vulnerable to each of the four social conditions under study than the affluent (Adler and Newman 2002; Benach et al. 2014; Levitt 1999; Reardon 2013), their average rating is likely to overestimate the true severity of social conditions by not accounting for the experience of the affluent. Conversely, the average affluent respondent would be expected to underestimate the true severity of social conditions by not accounting for the experience of the non-affluent, leaving the objective reality in between the perceptions of the two groups. The affluent’s tendency to underestimate the objective severity of social conditions may increase as their isolation from the non-affluent increases, a hypothesis that warrants investigation in future research.
I also check to see that results are consistent when the full range of the variable is used.
The diversity of Americans’ voluntary activity is also reflected in data collected by the Corporation for National and Community Service. Among those who volunteered with a group or organization, most volunteered with religious organizations (36 %), followed by educational and youth service organizations (27 %), with social or community service organizations—the category most directly related to addressing harmful social conditions—coming in third at 14 % (CNCS 2010).
Results for voter registration and voter turnout should be interpreted in light of the finding that over-reporting often biases self-reported measures of electoral participation (Bernstein et al. 2001). Ninety-six percent of affluent respondents report being registered to vote, while 88 % of affluent respondents in the SOTC survey report voting in a local election in the last 12 months. This issue is not unique to the SOTC survey: In the 1990 American Citizen Participation Study, one of the few other surveys to ask about voting in local elections, 80 % of affluent respondents (with incomes adjusted for year) report having voted in a “local community election.” By comparison, the best available data (see Oliver et al. 2012, p. 65) suggest that actual turnout in local elections for all social class groups ranges from below 35 % when there is no concurrent federal election to upwards of 75 % when there is a concurrent presidential election (there is no available data with which to measure actual turnout in local elections among the affluent in particular).
Measures of individual-level partisanship and ideology are not available in the Soul of the Community survey. I note that past studies of the effects of economic segregation have not included either as controls (Oliver 1999). I also test for bias from the omission of these controls by rerunning the main analyses controlling on whether a respondent lives in a “red state” or a “blue state” as a proxy for individual-level partisanship and ideology (see Supplementary material Appendix p. 16).
The lowest level of geo-coding available in the survey is the county.
Two SOTC communities, Miami, FL, and Palm Beach, FL, share the same MSA.
In measuring the isolation index, affluence is defined as having an income larger than four times the poverty threshold for a family of four ($20,650), making the limit $82,600.
Class isolation and income inequality are only moderately correlated among the MSAs in the dataset, preventing issues with multicollinearity (Supplementary material Appendix p. 6).
Results are identical in direction and significance with and without standardized non-binary independent variables.
The same also holds true in a multilevel ordered logit model.
An alternative interpretation of these results is that respondents are ignoring the survey taker’s instructions (p. 10) by providing ratings of the crime level that are only meant to apply to their neighborhood rather than their larger metropolitan community, leading to a strong relationship between Neighborhood Experience and perceptions of crime. If this were the case, respondents could not be said to be extrapolating from neighborhood conditions to form perceptions of social conditions. Yet this alternative interpretation is contradicted by results showing that MSA-level factors, most notably Percent Black, also have significant effects on crime perceptions. Respondents appear to be taking MSA-level factors into account in rating the crime level, suggesting that they are complying with the instructions to provide ratings that apply to their larger metropolitan community rather than their neighborhood alone.
See p. 20 in the Supplementary material Appendix for regression results from the fixed effects model.
The regression results from which this figure is derived are available in the Supplementary material Appendix (p. 21).
The effect of class isolation on group membership is also null when the full range of the variable is included in a multilevel linear model (B = −0.04, p = 0.40).
I note that the effect of class isolation on voter registration is no longer significant (B = 0.07, p = 0.43) when state-level partisanship is added as a control (see Supplementary material Appendix p. 19). This suggests that electoral context may matter more than class context in sha** this outcome. All other results are consistent when state-level partisanship is controlled for.
References
Adler, N. E., & Newman, K. (2002). Socioeconomic disparities in health: Pathways and policies. Health Affairs, 21(2), 60–76.
Atkinson, R. (2008). The great cut: The support for private modes of social evasion by public policy. Social Policy & Administration, 42(6), 593–610.
Bartels, L. M. (2008). Unequal democracy: The political economy of the new gilded age. New York: Russell Sage Foundation.
Benach, J., Vives, A., Amable, A., Vanroelen, C., Tarafa, G., & Muntaner, C. (2014). Precarious employment: Understanding an emerging social determinant of health. Annual Review of Public Health, 35, 229–253.
Bernstein, R., Chadha, A., & Montjoy, R. (2001). Overreporting voting: Why it happens and why it matters. Public Opinion Quarterly, 65(1), 22–44.
Blumer, H. (1971). Social problems as collective behavior. Social Problems, 18(3), 298–306.
Carnes, N. (2013). White-collar government: The hidden role of class in economic policy making. Chicago: University of Chicago Press.
Corporation for National and Community Service. (2010). Civic life in America: Key findings on the civic health of the nation. Washington, DC: Corporation for National and Community Service.
Cruces, G., Perez-Truglia, R., & Tetaz, M. (2013). Biased perceptions of income distribution and preferences for redistribution: Evidence from a survey experiment. Journal of Public Economics, 98, 100–112.
Dawson, M. C. (1994). Behind the mule: Race and class in African-American politics. Princeton: Princeton University Press.
de Tocqueville, A. (2003). Democracy in America. London: Penguin Books.
Dreier, P., Mollenkopf, J. H., & Swanstrom, T. (2013). Place matters: Metropolitcs for the twenty-first century. Lawrence, Kan.: University Press of Kansas.
Elo, I. T., Mykyta, L., Margolis, R., & Culhane, J. F. (2009). Perceptions of neighborhood disorder: The role of individual and neighborhood characteristics. Social Science Quarterly, 90(5), 1298–1320.
Eulau, H. (1986). Politics, self, and society: A theme and variations. Cambridge: Harvard University Press.
Gainsborough, J. F. (2001). Fenced off: The suburbanization of American politics. Washington, DC: Georgetown University Press.
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press.
Gilens, M. (2012). Affluence and influence: Economic inequality and political power in America. Princeton: Princeton University Press.
Hilgartner, S., & Bosk, C. L. (1988). The rise and fall of social problems: A public arenas model. American Journal of Sociology, 94(1), 53–78.
Hopkins, D. J. (2010). Politicized places: Explaining where and when immigrants provoke local opposition. American Political Science Review, 104(1), 40–60.
Huckfeldt, R. (1984). Political loyalties and social class ties: The mechanisms of contextual influence. American Journal of Political Sciecne, 28(2), 399–417.
Key, V. O. (1949). Southern politics: In state and nation. New York: Vintage Books.
Kluegel, J. R., Tilly, C., & Bobo, L. D. (2001). Perceived group discrimination and policy attitudes: The sources and consequences of the race and gender gaps. In L. Bobo & A. O’Connor (Eds.), Urban inequality: Evidence from four cities (pp. 163–198). New York: Russel Sage Foundation.
Kneebone, E., & Berube, A. (2013). Confronting suburban poverty in America. Washington, DC: Brookings Institution Press.
Krivo, L. J., Washington, H. M., Peterson, R. D., Browning, C. R., Calder, C. A., & Kwan, M.-P. (2013). Social isolation of disadvantage and advantage: The reproduction of inequality in urban space. Social Forces, 92(1), 141–164.
Levine, A. S. (2015). American insecurity: Why our economic fears lead to political inaction. Princeton: Princeton University Press.
Levitt, S. D. (1999). The changing relationship between income and crime victimization. Federal Reserve Bank of New York Economic Policy Review, 5(3), 87–98.
Logan, J. R. (2011). Separate and unequal: The neighborhood gap for Blacks, Hispanics and Asians in metropolitan America. US2010 Project.
Massey, D. S., Albright, L., Casciano, R., Derickson, E., & Kinsey, D. N. (2013). Climbing Mount Laurel: The struggle for affordable housing and social mobility in an American suburb. Princeton: Princeton University Press.
Massey, D. S., & Denton, N. A. (1988). The dimensions of residential segregation. Social Forces, 67(2), 281–315.
Massey, D. S., & Denton, N. A. (1993). American apartheid: Segregation and the making of an underclass. Cambridge: Harvard University Press.
McCall, L. (2013). The undeserving rich: American beliefs about inequality, opportunity, and redistribution. New York: Cambridge University Press.
McCarty, N. M., Poole, K. T., & Rosenthal, H. (2006). Polarized America: The dance of ideology and unequal riches. Cambridge: MIT Press.
Michener, J. (2013). Neighborhood disorder and local participation: Examining the political relevance of “broken windows”. Political Behavior, 35(4), 777–806.
Mooney, L. A., Knox, D., & Schacht, C. (2012). Understanding social problems. Belmont: Wadsworth Publishing.
Newman, B. J., Johnston, C. D., & Lown, P. L. (2015). False consciousness or class awareness? Local income inequality, personal economic position, and belief in American meritocracy. American Journal of Political Science, 59(2), 326–340.
Oliver, J. E. (1999). The effects of metropolitan economic segregation on local civic participation. American Journal of Political Science, 43(1), 186–212.
Oliver, J. E. (2001). Democracy in suburbia. Princeton: Princeton University Press.
Oliver, J. E., Ha, S. E., & Callen, Z. (2012). Local elections and the politics of small-scale democracy. Princeton: Princeton University Press.
Oliver, J. E., & Mendelberg, T. (2000). Reconsidering the environmental determinants of white racial attitudes. American Journal of Political Science, 44(3), 574–589.
Putnam, R. D. (2015). Our kids: The American Dream in crisis. New York: Simon & Schuster.
Reardon, S. (2013). The widening income achievement gap. Educational Leadership, 70(8), 10–16.
Reardon, S. F., & Bischoff, K. (2011). Income inequality and income segregation. American Journal of Sociology, 116(4), 1092–1153.
Redlawsk, D. P., & Lau, R. R. (2013). Behavioral decision-making. In L. Huddy, D. O. Sears, & J. S. Levy (Eds.), The Oxford handbook of political psychology (pp. 130–164). New York: Oxford University Press.
Reich, R. (2006). Philanthropy and its uneasy relation to equality. In W. Damon & S. Verducci (Eds.), Taking philanthropy seriously: Beyond noble intentions to responsible giving (pp. 33–49). Bloomington: Indiana University Press.
Ridgeway, C. L., & Fisk, S. R. (2012). Class rules, status dynamics, and gateway interactions. In S. R. Fisk, S. T. Fiske, & H. R. Markus (Eds.), Facing social class: Social psychology of social class, essay (pp. 131–151). New York: Russel Sage Foundation.
Rose, M., & Baumgartner, F. R. (2013). Framing the poor: Media coverage and U.S. poverty policy, 1960–2008. Policy Studies Journal, 41(1), 22–53.
Rossi, P. H. (1980). Why families move. Beverly Hills: Sage.
Rothwell, J. (2012). Housing costs, zoning, and access to high-scoring schools. Metropolitan Policy Program at Bookings.
Rothwell, J. T., & Massey, D. S. (2010). Density zoning and class segregation in U.S. metropolitan areas. Social Science Quarterly, 91(5), 1123–1143.
Sandy, J., & Duncan, K. (2010). Examining the achievement test score gap between urban and suburban students. Education Economics, 18(3), 297–315.
Schlozman, K. L., Verba, S., & Brady, H. E. (2012). The unheavenly chorus: Unequal political voice and the broken promise of American democracy. Princeton: Princeton University Press.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 677–695.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.
Verba, S., Schlozman, K. L., & Brady, H. E. (1995). Voice and equality: Civic voluntarism in American politics. Cambridge: Harvard University Press.
Widestrom, A. (2015). Displacing democracy: Economic segregation in America. Philadelphia: University of Pennsylvania Press.
Wilkinson, R. G., & Pickett, K. (2010). The spirit level: Why greater equality makes societies stronger. New York: Bloomsbury Press.
Acknowledgment
I would like to thank Tali Mendelberg for her guidance throughout this project, and Martin Gilens for helpful feedback. I would also like to thank Douglas Massey and his co-author Jacob Rugh for providing me with data on class isolation. Finally, I would like to thank Mary Kroeger, Vladimir Medenica, Katherine McCabe, participants in the Princeton American Politics Graduate Research Seminar, and participants in the Princeton American Political Behavior Workshop for their comments. The data and code necessary to replicate the results in this paper are available in the Political Behavior Dataverse: https://www.dataverse.harvard.edu/dataverse/polbehavior.
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Thal, A. Class Isolation and Affluent Americans’ Perception of Social Conditions. Polit Behav 39, 401–424 (2017). https://doi.org/10.1007/s11109-016-9361-9
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DOI: https://doi.org/10.1007/s11109-016-9361-9