IBSS: Measuring Justice, Managing Equity: An Interdisciplinary, Multi-Level Approach to Understanding Bias and Equity in Police Stops and Use of Force

IBSS：衡量正义，管理公平：理解警察拦截和使用武力中的偏见和公平的跨学科、多层次方法

• 批准号: 1329162
• 负责人: Phillip Goff
• 金额: $ 100万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329162&HistoricalAwards=false
• 关键词: IBSS; Measuring; Justice; Managing; Equity

This project focuses on what causes racial disparities in policing and how one can measure these disparities using tools taken from sociology, demography, public policy, criminology, psychology, and behavioral economics. Understanding what causes contemporary racial inequality is particularly vexing for researchers across disciplines because the US's steady decline in racial prejudice has not been accompanied by an analogous decline in racial inequality across social institutions (e.g., education, healthcare, employment, criminal justice). This has meant that traditional theories of how racial inequality is produced are insufficient to explain contemporary racial dynamics, requiring new research models to produce new understandings of social inequality. This project capitalizes on existing research collaborations between the Consortium for Police Leadership in Equity and law enforcement departments across the US to produce a mixed-methods approach to understanding what produces racial inequality in complex systems (i.e., policing). In cooperation with approximately 25 law enforcement partners, the investigators will first standardize data collection regarding police stops of pedestrians and motorists as well as police use of force. Second, researchers will collect psychological surveys from officers, aggregating responses by districts within departments. Finally, using social-spatial data, department policy data, aggregate officer attitude data, and data about the relative contributions of "bad apples" to department-wide disparity rates, the researchers will address some of the fundamental questions about race in law enforcement as well as the role that local demographics and department-wide culture have in producing racial inequality. The interdisciplinary research team and large number of participating police departments facilitate inquiry across multiple levels of analysis and comparisons across different types of departments, producing a symptomology of unequal outcomes. While previous research has looked at police-citizen encounters (stops, searches, arrests, force, etc.) or measured biases, it has rarely done both together. Consequently, this project will contribute both to scientific understandings of what causes racial inequality in policing and identifying ways practitioners can measure and manage that inequality.Taken together, the investigators intend this project to promote the development and validation of a nationally standardized approach to police stops and use of force data collection, analysis, and interpretation. The findings will be widely disseminated to police departments, directly informing policy and setting the scientific foundations for national best practices to reduce racial inequality in police outcomes. This project will also provide postdoctoral fellows and graduate students a unique opportunity to examine racial bias in an applied and multidisciplinary context, while exposing them to more complex and diverse data analytic strategies. This project is supported through the NSF Interdisciplinary Behavioral and Social Sciences Research (IBSS) competition.

这个项目的重点是什么原因导致警务种族差异，以及如何使用社会学，人口学，公共政策，犯罪学，心理学和行为经济学的工具来衡量这些差异。 理解当代种族不平等的原因对于跨学科的研究人员来说尤其令人烦恼，因为美国种族偏见的稳步下降并没有伴随着种族不平等在社会机构中的类似下降（例如，教育、医疗保健、就业、刑事司法）。 这意味着传统的关于种族不平等如何产生的理论不足以解释当代的种族动态，需要新的研究模型来产生对社会不平等的新理解。 该项目利用了美国警察平等领导联盟和执法部门之间现有的研究合作，以产生一种混合方法来理解复杂系统中产生种族不平等的原因（即，警务）。 调查人员将与大约25个执法伙伴合作，首先规范有关警察拦截行人和驾车者以及警察使用武力的数据收集。 其次，研究人员将收集官员的心理调查，汇总部门内各区的反应。 最后，使用社会空间数据，部门政策数据，汇总官员态度数据，以及有关“坏苹果”对部门差异率的相对贡献的数据，研究人员将解决一些关于执法中种族的基本问题，以及当地人口统计和部门文化在产生种族不平等方面的作用。 跨学科研究小组和大量参与的警察部门促进了跨多个层次的分析和不同类型部门之间的比较，产生了不平等结果的系统学。 虽然以前的研究着眼于警察与公民的接触（停止，搜查，逮捕，武力等）。或测量偏差，它很少同时做到这两点。 因此，这个项目将有助于科学的理解是什么原因导致种族不平等的警务和确定从业人员可以测量和管理的不平等。两者合计，调查人员打算这个项目，以促进发展和验证的国家标准化的方法，警察停止和使用武力的数据收集，分析和解释。调查结果将广泛传播给警察部门，直接为政策提供信息，并为减少警察结果中的种族不平等的国家最佳做法奠定科学基础。该项目还将为博士后研究员和研究生提供一个独特的机会，在应用和多学科背景下研究种族偏见，同时使他们接触到更复杂和多样化的数据分析策略。该项目通过NSF跨学科行为和社会科学研究（IBSS）竞赛获得支持。