The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Spatial Segmentation and the Black Middle Class
Abstract
Ethnographic studies of the black middle class focus attention on the ways in which residential environments condition the experiences of different segments of the black class structure. This study places these arguments in a larger demographic context by providing a national analysis of neighborhood inequality and spatial inequality of different racial and ethnic groups in urban America. The findings show that there has been no change over time in the degree to which majority-black neighborhoods are surrounded by spatial disadvantage. Predominantly black neighborhoods, regardless of socioeconomic composition, continue to be spatially linked with areas of severe disadvantage. However, there has been substantial change in the degree to which middle- and upper-income African-American households have separated themselves from highly disadvantaged neighborhoods. These changes are driven primarily by the growing segment of middle- and upper-income African-Americans living in neighborhoods in which they are not the majority group, both in central cities and in suburbs.
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“Majority Black neighborhoods were so substantially segregated and poverty so concentrated within them that even Black residents with an annual income of $100,000 or more a year lived with higher levels of neighborhood disadvantage (e.g., poor public school funding, poor housing, lowered grocery options) than White families earning less than a 1/3rd of that amount (Sharkey, 2014).”
From On race, human variation, and who gets and dies of sepsis (2022) · cites this paper as Sharkey, 2014
In the citing paper
“In a nationwide analysis of neighborhood and spatial inequality of US census tracts and households, Sharkey (2014) found that no matter the socioeconomic configuration, majority Black neighborhoods were more often physically close to regions that were severely disadvantaged.”
From On race, human variation, and who gets and dies of sepsis (2022) · cites this paper as Sharkey, 2014
Citations
Cites
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Anselin, L. (1988) · Studies in Operational Regional Science · doi:10.1007/978-94-015-7799-1 · Cited by 9,274
Noble, C. (1988) · American Political Science Review · doi:10.2307/1961794 · Cited by 6,176
Assessing “Neighborhood Effects”: Social Processes and New Directions in Research
Sampson, R. J., Morenoff, J. D., & Gannon-Rowley, T. (2002) · Annual Review of Sociology · doi:10.1146/annurev.soc.28.110601.141114 · Cited by 4,075
Experimental Analysis of Neighborhood Effects
Kling, J. R., Liebman, J. B., & Katz, L. F. (2007) · Econometrica · doi:10.1111/j.1468-0262.2007.00733.x · Cited by 2,719
GeoDa: An Introduction to Spatial Data Analysis
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Beyond Social Capital: Spatial Dynamics of Collective Efficacy for Children
Sampson, R. J., Morenoff, J. D., & Earls, F. J. (1999) · American Sociological Review · doi:10.2307/2657367 · Cited by 2,142
NEIGHBORHOOD INEQUALITY, COLLECTIVE EFFICACY, AND THE SPATIAL DYNAMICS OF URBAN VIOLENCE*
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Research works printed but not linked: 12
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- Drake St., 1945, Cayton
- Haynes Bruce D, Red Lines
- Isaacs Julia B, Pp. 81–90 in Getting Ahead or Losing Ground: Economic Mobility in America
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Cited by
On race, human variation, and who gets and dies of sepsis
Brinkworth, J. F., & Shaw, J. G. (2022) · American Journal of Biological Anthropology · doi:10.1002/ajpa.24527 · Cited by 9
Harding, D., Sanbonmatsu, L., Duncan, G., Gennetian, L., Katz, L., Kessler, R., Kling, J., Sciandra, M., & Ludwig, J. (2021) · doi:10.3386/w28454 · Cited by 7
Metadata
- Authors
- Sharkey, P.
- Venue
- American Journal of Sociology
- Publisher
- University of Chicago Press
- Published
- 2014-01
- Volume
- 119
- Issue
- 4
- Pages
- 903-954
- ISSN
- 0002-9602
- 1537-5390
- Cited by
- 101
- References
- 65
- Language
- en
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
