Risk-based policing [electronic resource] : evidence-based crime prevention with big data and spatial analytics / Leslie W. Kennedy, Joel M. Caplan, Eric L. Piza.
- 作者： Kennedy, Leslie W.
- 其他作者：
- 出版： Oakland, Ca. : University of California Press c2018.
- 主題： Crime prevention--Case studies. , Crime analysis--Data processing.
- 版本：1st ed.
- ISBN： 9780520968349 (electronic book) 、 0520968344 (electronic book)
- URL：
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- 一般註：Includes bibliographical references and index. Introduction to risk and big data -- Evolution of modern policing -- Policing in the new era of public safety and law enforcement -- Risk-based policing and action -- The theory of risky places -- High-risk target areas and priority places -- Case studies of Colorado Springs, Glendale, Newark, and Kansas city : the role of police in risk-based policing -- Facilitators and impediments to designing, implementing, and evaluating risk-based policing strategies : insights from completed researcher-practitioner partnerships -- The roles of multiple stakeholders in risk-based policing : case studies of Jersey city and Atlantic city -- People make risk-based policing and data actionable. 110年度臺灣學術電子書暨資料庫聯盟採購
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讀者標籤：
- 系統號： 000291759 | 機讀編目格式
館藏資訊
Risk-based policing is a research advancement that improves public safety, and its applications prevent crime specifically by managing crime risks. In Risk-Based Policing, the authors analyze case studies from a variety of city agencies including Atlantic City, New Jersey; Colorado Springs, Colorado; Glendale, Arizona; Kansas City, Missouri; Newark, New Jersey; and others. They demonstrate how focusing police resources on risky places and basing police work on smart uses of data can address the worst effects of disorder and crime while improving community relations and public safety. Topics include the role of big data; the evolution of modern policing; dealing with high-risk targets; designing, implementing, and evaluating risk-based policing strategies; and the role of multiple stakeholders in risk-based policing. The book also demonstrates how risk terrain modeling can be extended to provide a comprehensive view of prevention and deterrence.
摘要註
"Risk-based policing is the latest advancement in the long history of policing innovations, where research and planning have combined to manage crime risks, prevent crime, and enhance public safety. In Risk-Based Policing the authors share case studies from different agencies to demonstrate how focusing police resources at risky places, based on smart uses of data and strong analytical work, can address the worst effects of disorder and crime while improving public safety and community relations. Topics include the role of big data; the evolution of modern policing; dealing with high-risk targets; designing, implementing, and evaluating risk-based policing strategies; and the role of multiple stakeholders in risk-based policing. Case studies explore cities such as Colorado Springs, Glendale, Newark, Kansas City, and others. The book also demonstrates how Risk Terrain Modeling (RTM) can be extended to offer a more comprehensive view of prevention and deterrence"--Provided by publisher.