Research SummaryWe conducted a group randomized‐controlled trial of an internal dashboard system deployed by the Michigan State Police to determine its effectiveness in reducing traffic stop racial disparities. Informed by a difference‐in‐differences design, analyses of traffic stop data from 2019–2022 indicated that the dashboard had no impact on traffic stop racial disparities. Additional analyses of traffic stops, crashes, and crime revealed that the dashboard had no “de‐policing” effect on traffic patrols, nor were there any significant changes in traffic safety or crime in treatment patrol areas relative to control patrol areas. Qualitative analyses of interview data from more than 40 troopers in the agency revealed unique barriers to program implementation and opportunities for future improvement.Policy ImplicationsIn an era of policing where the capacity and demand for data‐driven decision‐making is on the rise, evidence‐based policy and practice can provide police agencies with informed solutions for addressing traffic stop racial disparities. Yet, the increased demand for evidence‐based reform is fueled by a relatively low supply of evidence‐based research. This study adds to this evidence base by providing unique insights into the effectiveness of a program built specifically to reduce racial disparities in traffic stops, while also highlighting implementation challenges.

中文翻译：

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尝试减少交通站点种族差异：内部仪表板干预的实验评估

研究摘要我们对密歇根州警察局部署的内部仪表板系统进行了一组随机对照试验，以确定其在减少交通堵塞种族差异方面的有效性。根据双重差异设计，对 2019 年至 2022 年交通站点数据的分析表明，仪表板对交通站点种族差异没有影响。对交通停车、碰撞和犯罪的额外分析表明，仪表板对交通巡逻没有“去警务”作用，相对于控制巡逻区域，处理巡逻区域的交通安全或犯罪也没有任何显着变化。对该机构 40 多名士兵的访谈数据进行定性分析，揭示了计划实施的独特障碍和未来改进的机会。政策含义在数据驱动决策的能力和需求不断上升的警务时代，证据-以此为基础的政策和实践可以为警察机构提供明智的解决方案，以解决交通站点种族差异问题。然而，基于证据的研究供应相对较少，推动了对基于证据的改革的需求增加。这项研究通过对专门为减少交通站点种族差异而制定的计划的有效性提供独特的见解，增加了这一证据基础，同时也强调了实施方面的挑战。