不可见的
统计鉴别
忽视
心理学
人口统计学的
社会心理学
选择(遗传算法)
人口
作文(语言)
基础(拓扑)
统计
计量经济学
人口学
计算机科学
数学
人工智能
社会学
哲学
数学分析
精神科
语言学
作者
David Hagmann,Gwendolin B. Sajons,Catherine H. Tinsley
标识
DOI:10.31219/osf.io/cnv45
摘要
Statistical discrimination relies on people inferring unobservable characteristics of group members based on their beliefs about the group. Across four pre-registered experiments (N = 9,002), we show that accurate information about the composition of top performers can induce incorrect beliefs about performance differences across groups when the groups are of unequal size. Because people fail to account for base rates, they underestimate the performance of members of smaller groups. As a result, when participants in our experiments receive true information about the gender composition of top performers in a male-dominated candidate pool, they are less likely to hire women, even when there are no gender differences in performance (Study 1). Similarly, they are less likely to hire better-performing non-White candidates when the racial demographics of the candidate pool reflect the US population (Study 4). We show that these choices reflect an error in statistical reasoning, rather than being motivated by a desire to discriminate against any particular group (Study 2). Despite leading to less accurate beliefs, given the choice, participants disproportionately seek out information about top performers and discrimination thus persists when information selection is endogenous (Study 3).
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