种族(生物学)
多样性(政治)
白色(突变)
精英
质量(理念)
心理学
不平等
考试(生物学)
公共关系
社会心理学
政治学
社会学
性别研究
数学分析
古生物学
生物化学
化学
哲学
数学
认识论
政治
生物
法学
基因
出处
期刊:Organization Science
[Institute for Operations Research and the Management Sciences]
日期:2022-02-11
卷期号:33 (6): 2364-2403
被引量:10
标识
DOI:10.1287/orsc.2021.1534
摘要
Universities and colleges often engage in initiatives aimed at enrolling students from diverse demographic groups. Although substantial research has explored the impact of such diversity initiatives, less understood is the extent to which certain application strategies may continue to favor historically privileged groups, especially white men, as they seek admission to selective programs. With this study, I begin to address this gap by investigating the gender and racial implications of application endorsements—a common, often informal, network practice of signaling support for certain applicants that is shown to significantly boost an applicant’s chances of admission. Using unique data on the applicants and matriculants to a full-time MBA program at one elite U.S. business school, I first assess whether the endorsement advantage differs across demographic groups. Building on the social networks, selection, and inequality literatures, I then identify and test three key theoretical mechanisms by which the endorsement process may potentially benefit white men more than women and racial minorities. Although I do not find evidence in the studied program that the application endorsement is valued differently by key admissions officers or that it provides a different quality signal depending on the applicant’s gender or race, I do find that white men are significantly more likely than women and minorities to receive application endorsements. I conclude by discussing the implications of this study for understanding how gender and racial differences in accessing advantageous (often informal) network processes may undermine organizational efforts to achieve demographic equality and diversity. Funding: Financial support from the James S. Hardigg (1945) Work and Employment Fund and the MIT Sloan School of Management is gratefully acknowledged.
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