Bibliographical Guide to Structural Racialization , Implicit Bias , and Systems Thinking

by author: We study race in the labor market by sending fictitious resumes to helpwanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-Americanor White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to still be prominent in the U.S. labor market. Conley, Dalton. Being Black, Living in the Red: Race, Wealth, and Social Policy in America. Berkeley: University of California Press, 1999. Guinier, Lani and Gerald Torres. The Miner's Canary: Enlisting Race, Resisting Power, Transforming Democracy. Cambridge: Harvard University Press, 2002. Kaufman, Robert. “Assessing Alternative Perspectives on Race and Sex Employment Segregation.” American Sociological Review 67 (2002): 547-72. Abstract by author: Four major explanations for employment segregation--skill deficits, worker preferences, economic and organizational structure, and stereotyping/queuing--are assessed using a diverse and overlapping set of predictors: general skills and training, product market structure, raceand sex-typed tasks and conditions, desirable employment and growth rates, and links to other labor market actors. A two-stage measurement and analytic strategy controls for relevant worker-level factors. Data from the 1990 census PUMs are analyzed to measure the employment segregation of black women, black men, and white women in relation to white men across 1,917 labor market positions, net of human capital, family structure, geographic residence and labor supply. Archival data provide measures of variables characterizing labor market positions. Stereotyping and queuing explanations are broadly consistent with nearly all results, while a worker preference approach applies to somewhat fewer predictors and is largely but not wholly compatible with their effects. A skill deficits explanation applies to, and is supported by, a narrow set of findings, while the economic and organizational structure explanations are restricted in their relevance and receive limited support.by author: Four major explanations for employment segregation--skill deficits, worker preferences, economic and organizational structure, and stereotyping/queuing--are assessed using a diverse and overlapping set of predictors: general skills and training, product market structure, raceand sex-typed tasks and conditions, desirable employment and growth rates, and links to other labor market actors. A two-stage measurement and analytic strategy controls for relevant worker-level factors. Data from the 1990 census PUMs are analyzed to measure the employment segregation of black women, black men, and white women in relation to white men across 1,917 labor market positions, net of human capital, family structure, geographic residence and labor supply. Archival data provide measures of variables characterizing labor market positions. Stereotyping and queuing explanations are broadly consistent with nearly all results, while a worker preference approach applies to somewhat fewer predictors and is largely but not wholly compatible with their effects. A skill deficits explanation applies to, and is supported by, a narrow set of findings, while the economic and organizational structure explanations are restricted in their relevance and receive limited support. Krivo, Lauren J. and Robert L. Kaufman. “Housing and Wealth Inequality: Racial-Ethnic Differences in Home Equity in the United States.” Demography 41 (2004): 585-605. Abstract by author: In our study, we took a first step toward broadening our understanding of the sources of both housing and wealth inequality by studying differences in housingby author: In our study, we took a first step toward broadening our understanding of the sources of both housing and wealth inequality by studying differences in housing