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警察特征与涉及警察的致命枪击事件中的种族差异。

Officer characteristics and racial disparities in fatal officer-involved shootings.

机构信息

Department of Psychology, University of Maryland at College Park, College Park, MD 20742;

Department of Psychology, Michigan State University, East Lansing, MI 48824.

出版信息

Proc Natl Acad Sci U S A. 2019 Aug 6;116(32):15877-15882. doi: 10.1073/pnas.1903856116. Epub 2019 Jul 22.

Abstract

Despite extensive attention to racial disparities in police shootings, two problems have hindered progress on this issue. First, databases of fatal officer-involved shootings (FOIS) lack details about officers, making it difficult to test whether racial disparities vary by officer characteristics. Second, there are conflicting views on which benchmark should be used to determine racial disparities when the outcome is the rate at which members from racial groups are fatally shot. We address these issues by creating a database of FOIS that includes detailed officer information. We test racial disparities using an approach that sidesteps the benchmark debate by directly predicting the race of civilians fatally shot rather than comparing the rate at which racial groups are shot to some benchmark. We report three main findings: 1) As the proportion of Black or Hispanic officers in a FOIS increases, a person shot is more likely to be Black or Hispanic than White, a disparity explained by county demographics; 2) race-specific county-level violent crime strongly predicts the race of the civilian shot; and 3) although we find no overall evidence of anti-Black or anti-Hispanic disparities in fatal shootings, when focusing on different subtypes of shootings (e.g., unarmed shootings or "suicide by cop"), data are too uncertain to draw firm conclusions. We highlight the need to enforce federal policies that record both officer and civilian information in FOIS.

摘要

尽管人们对警察枪击事件中的种族差异给予了广泛关注,但有两个问题阻碍了这一问题的进展。首先,涉及致命警官枪击事件(FOIS)的数据库缺乏有关警官的详细信息,这使得很难测试警官特征是否会导致种族差异。其次,对于使用哪种基准来确定种族群体成员被致命枪击的比率存在冲突的观点,当结果是种族群体被致命枪击的比率时。我们通过创建一个包含详细警官信息的 FOIS 数据库来解决这些问题。我们使用一种方法来测试种族差异,该方法通过直接预测被致命枪击的平民的种族来避免基准辩论,而不是将种族群体被枪击的比率与某个基准进行比较。我们报告了三个主要发现:1)在 FOIS 中,黑人和西班牙裔警官的比例增加,被枪击的人更有可能是黑人或西班牙裔,而不是白人,这种差异可以用县人口统计学来解释;2)特定种族的县级暴力犯罪强烈预测被枪击的平民的种族;3)尽管我们没有发现致命枪击事件中存在反黑人或反西班牙裔的种族差异的总体证据,但当我们关注不同类型的枪击事件(例如,非武装枪击事件或“警察自杀”)时,数据不够确定,无法得出确凿的结论。我们强调需要执行联邦政策,在 FOIS 中记录警官和平民的信息。

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