使用不一致的种族观念进行种族偏见测试
1Department of Computer Science, Cornell University, Ithaca, NY, USA.
Science advances
|November 19, 2025
概括
这项研究引入了一种新的方法来测试种族偏见,通过观察个人如何被对待,当他们的种族被认为是不同的. 研究人员发现,当被认为是西班牙裔与白人相比,警察更有可能搜查或逮捕司机.
科学领域:
- 社会心理学 社会心理学
- 犯罪学 犯罪学
- 数据科学数据科学数据科学
背景情况:
- 治疗中的种族偏见通常通过比较不同个体来评估,这是由于混因素而具有挑战性的.
- 现有的方法很难将种族作为影响治疗差异的唯一变量来孤立.
研究的目的:
- 开发和应用一种用于检测种族偏见的新型测试,克服了比较不同个体的局限性.
- 为了评估警察交通停车场的种族偏见,使用一种专注于同一个人被视为不同种族的方法.
主要方法:
- 提出了一项新的偏见测试,评估当他们的种族被认为不同时,对同一个人的差异性待遇.
- 将该方法应用于警方的交通拦截数据,根据司机的感知种族分析结果.
- 专注于身份数据被感知而不是自我报告的场景,并多次观察个人.
主要成果:
- 与被认为是白人相比,被认为是西班牙裔的司机更有可能被警察搜查或逮捕.
- 拟议的方法成功地确定了与交通停车场感知种族相关的差异性待遇.
结论:
- 新型偏见测试在确定现实世界场景中的种族差异方面是有效的,比如警察拦截交通.
- 这种方法广泛适用于具有感知身份数据的数据集,为在各种环境中检测偏见提供了强大的工具.
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