Workshop on Decision Analytics for Dynamic Policing; Arlington, Virginia; May 9-10, 2019

动态警务决策分析研讨会；

• 批准号: 1917624
• 负责人: Victoria Chen
• 金额: $ 5万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1917624&HistoricalAwards=false
• 关键词: Workshop; Decision; Analytics; Dynamic; Policing

This award supports a conference that convenes researchers from the fields of operations engineering and criminal justice, along with police department leadership from across the US, to explore research directions in decision analytics and operations research to improve dynamic, data-driven policing methods. Beginning in 2008, so-called "predictive policing", which entails using analytical methods to predict how, when, where, and by whom crimes will occur, has been deployed by police departments in many states. These methods rely on historical data collected on time, location, and details of crimes, as well as on characteristics of perpetrators and victims. While some jurisdiction have shown an overall decrease in crime after implementation of predictive policing, other evaluative studies have shown the effects to be negligible or even detrimental. These methods have been criticized on three critical aspects: (1) they are not informed by a sociological perspective; (2) they assume that data include the necessary information for both prediction and effective response; and (3) they ignore the dynamic nature of the policing system. This conference will bring together appropriate researchers, along with practitioners, to build a cross-disciplinary understanding of policing challenges that may be addressable by decision analytics and operations research.One of the most serious challenges facing police departments is the effective use of resources to address calls for service, especially when responding to serious crimes. Police departments recognize that part of a comprehensive approach to community safety involves protecting the rights of all involved during police encounters. The focus of this workshop is on identifying operational aspects, including data collection and analysis, planning, training, and crime scene investigation, where additional research may lead to improved resource allocation. Day 1 of the conference includes keynotes on predictive policing and data analytic case studies, as well as breakout sessions for working groups. Day 2 of the conference will include a keynote speaker addressing international policing strategies, and working groups will continue to discuss and document research needs. Four teams of researchers who have established relationships with large police organizations serve as workshop organizers. Additional teams of attendees (operations engineers, criminal justice researchers, police department leadership) will be recruited to participate in the workshop. This activity will provide a unique forum to bring together a variety of stakeholders to encourage research on this important societal topic.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.

该奖项支持召开一次会议，召集来自运营工程和刑事司法领域的研究人员，以及来自美国各地的警察部门领导层，探索决策分析和运营研究的研究方向，以改进动态的、数据驱动的警务方法。从2008年开始，许多州的警察部门部署了所谓的“预测性警务”，即使用分析方法预测犯罪将如何、何时、何地和由谁发生。这些方法依赖于收集的关于犯罪时间、地点和细节的历史数据，以及犯罪者和受害者的特征。虽然一些司法管辖区在实施预测性警务后犯罪率总体下降，但其他评估研究表明，影响微不足道，甚至是有害的。这些方法在三个关键方面受到了批评：(1)它们没有从社会学的角度得到信息；(2)它们假定数据包括预测和有效应对的必要信息；(3)它们忽视了警察系统的动态性质。这次会议将把适当的研究人员和从业人员聚集在一起，以建立对警务挑战的跨学科理解，这些挑战可能通过决策分析和运筹学来解决。警察部门面临的最严重挑战之一是有效利用资源来满足服务要求，特别是在应对严重犯罪时。警察部门认识到，社区安全综合办法的一部分涉及在警察相遇期间保护所有相关人员的权利。该讲习班的重点是确定业务方面，包括数据收集和分析、规划、培训和犯罪现场调查，在这些方面进行更多的研究可能有助于改进资源分配。会议的第一天包括关于预测性警务和数据分析案例研究的主旨发言，以及工作组的分组会议。会议第二天将有一位主旨演讲人就国际警务战略发表讲话，各工作组将继续讨论和记录研究需要。与大型警察组织建立了关系的四个研究小组担任研讨会的组织者。将招募更多的参加者小组(业务工程师、刑事司法研究人员、警察部门领导)参加讲习班。这一活动将提供一个独特的论坛，将各种利益相关者聚集在一起，鼓励对这一重要社会主题的研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。