Doctoral Dissertation Research: The Geography of Stop and Frisk in Nine U.S. Cities

美国各地的警察机构都采用拦截搜身的做法，作为积极打击犯罪战略的一部分。这些策略受到批评，因为它们不成比例地牵连到黑人和拉丁裔个人，往往集中在有色人种的贫困社区，有时还涉及拘留从未被捕的人。然而，现有的社会科学研究并没有充分解释为什么一些社区比其他社区经历更多的拦截和搜身活动。此外，它没有考虑到主动警务的地理差异与法律决策的关系。这是一个重要的问题，因为法律学者认为，第四修正案法理学的发展导致了在贫穷的少数族裔社区进行拦截的门槛低于白人更富裕的地区。目前的研究试图通过以下方法来解决这些差距：(1)检查哪些社会过程导致了人口普查区截停搜身的地理差异，并确定“监控热点”的特征；(2)调查在被认为是“高犯罪率”的地区，证明截停的法律标准是否宽松。本研究将通过探索这些不平等的根源，扩大对刑事司法系统不平等的理解。为了实现这些目标，研究人员结合了三种类型的数据来分析这些关系，包括：(1)行人停车和搜身事件，(2)犯罪事件，(3)人口普查和美国社区调查的人口数据。第一阶段将利用来自美国9个城市（奥斯汀、波士顿、芝加哥、丹佛、新奥尔良、纽约、费城、旧金山和华盛顿特区）的数据，确定与“监控热点”相关的社区特征和社会过程——这些地区经历了异常高度集中的拦截和搜身活动。这一阶段的分析包括估计固定效应普通最小二乘和地理加权回归模型。第二阶段利用两个城市（芝加哥和纽约）行人停车基地的详细信息，评估在人口普查区进行停车的法律门槛是否系统性地有所不同。第二阶段的分析包括估算空间回归模型，通过分析社区边缘性、合理怀疑理由和逮捕率之间的关系来评估社区在法律门槛上的变化。这项研究的结果将揭示导致不公平警务的宏观社会进程，执法机构可以利用这些结果制定加强警察与社区关系的做法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Police agencies across the United States employ stop and frisk practices as part of a proactive crime-fighting strategy. These tactics are criticized because they disproportionately implicate Black and Latinx individuals, tend to be concentrated in poor neighborhoods of color, and sometimes involve the detainment of people who are never arrested. However, existing social science scholarship does not adequately address why some neighborhoods experience more stop and frisk activity than others. Moreover, it fails to consider the ways that geographic variation in proactive policing are related to legal decision-making. This is an important question because legal scholars argue that developments in Fourth Amendment jurisprudence have resulted in a threshold for conducting stops that is lower in poor, minority neighborhoods than in Whiter, more affluent areas. The present research seeks to address these gaps by: (1) examining which social processes generate geographic variation in stop and frisk across census tracts and identifying characteristics of "surveillance hotspots," and (2) investigating whether the legal standards for justifying stops are relaxed in perceived "high-crime" areas. This study will broaden understanding of inequality in the criminal justice system by exploring the roots of these inequalities.To achieve these aims, the researcher combines three types of data to analyze these relationships, including: (1) pedestrian stop and frisk incidents, (2) crime incidents, and (3) demographic data from the Census and American Community Survey. Stage one will utilize data from nine cities across the United States (Austin, Boston, Chicago, Denver, New Orleans, New York City, Philadelphia, San Francisco, and Washington, D.C.) to identify the neighborhood characteristics and social processes associated with "surveillance hotspots"--those areas that experience exceptionally high concentrations of stop and frisk activity. Analyses for this stage consist of estimating fixed-effects ordinary least squares and geographically weighted regression models. The second stage draws on detailed information about the bases for pedestrian stops in two cities (Chicago and New York City) to evaluate whether the legal thresholds for conducting stops systematically varies across census tracts. Analyses for stage two involve estimating spatial regression models to evaluate neighborhood-level variation in legal thresholds for making stops by analyzing the relationships between neighborhood marginality, reasonable suspicion justifications, and arrest rates. The findings from this study will shed light on the macro-level social processes that lead to inequitable policing and could be utilized by law enforcement agencies to develop practices that enhance police-community relations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.