An analysis of the New York City Police Department's "Stop-and-Frisk" policy in the context of claims of racial bias

被引:552
作者
Gelman, Andrew [1 ]
Fagan, Jeffrey
Kiss, Alex
机构
[1] Columbia Univ, Dept Polit Sci, New York, NY 10027 USA
[2] Columbia Univ, Sch Publ Hlth, New York, NY 10027 USA
[3] Columbia Univ, Sch Law, New York, NY 10027 USA
[4] Columbia Univ, Dept Stat, New York, NY 10027 USA
[5] Sunnybrook & Womens Coll Hlth Sci Ctr, Dept Res Design & Biostat, Toronto, ON, Canada
基金
美国国家科学基金会;
关键词
criminology; hierarchical model; multilevel model; overdispersed Poisson regression; police stops; racial bias;
D O I
10.1198/016214506000001040
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Recent studies by police departments and researchers confirm that police stop persons of racial and ethnic minority groups more often than whites relative to their proportions in the population. However, it has been argued that stop rates more accurately reflect rates of crimes committed by each ethnic group, or that stop rates reflect elevated rates in specific social areas, such as neighborhoods or precincts. Most of the research on stop rates and police-citizen interactions has focused on traffic stops, and analyses of pedestrian stops are rare. In this article we analyze data from 125,000 pedestrian stops by the New York Police Department over a 15-month period. We disaggregate stops by police precinct and compare stop rates by racial and ethnic group, controlling for previous race-specific arrest rates. We use hierarchical multilevel models to adjust for precinct-level variability, thus directly addressing the question of geographic heterogeneity that arises in the analysis of pedestrian stops. We find that persons of African and Hispanic descent were stopped more frequently than whites, even after controlling for precinct variability and race-specific estimates of crime participation.
引用
收藏
页码:813 / 823
页数:11
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