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E-grāmata: Risk-Based Policing: Evidence-Based Crime Prevention with Big Data and Spatial Analytics

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  • Formāts: 168 pages
  • Izdošanas datums: 20-Nov-2018
  • Izdevniecība: University of California Press
  • Valoda: eng
  • ISBN-13: 9780520968349
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Risk-Based Policing: Evidence-Based Crime Prevention with Big Data and Spatial AnalyticsPalielināt
  • Formāts: 168 pages
  • Izdošanas datums: 20-Nov-2018
  • Izdevniecība: University of California Press
  • Valoda: eng
  • ISBN-13: 9780520968349
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"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.

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.
Preface ix
Acknowledgments xi
PART 1 THE BASIC PRINCIPLES OF RISK-BASED POLICING
1 Introduction to Risk and Big Data
5(6)
Introduction to Risk-Based Policing in Crime Prevention
5(1)
The Importance of Risk
6(2)
Big Data
8(1)
Risk-Based Policing
8(1)
Conclusion
9(2)
2 The Evolution of Modern Policing
11(12)
Introduction
11(2)
Police Reform and Professionalization
13(3)
From Professionalism to Problem-Solving
16(2)
The Importance of Places and Data Analysis in Contemporary Policing
18(3)
Conclusion
21(2)
3 Policing in the New Era of Public Safety and Law Enforcement
23(12)
Focus on Places with Risk Terrain Modeling
23(4)
The Central Tenets of Risk-Based Policing
27(1)
Develop Spatial Risk Narratives
27(1)
Solicit and Value Input from Multiple Stakeholders
28(2)
Make Data-Driven Decisions
30(1)
Balance Strategies for Crime Risk Reduction
31(1)
Conclusion
32(3)
4 Risk-Based Policing and ACTION
35(18)
Introduction
35(1)
Risk Governance and the Police Leader
36(1)
ACTION Meetings
36(3)
A Detailed Breakdown of the ACTION Agenda
39(4)
The Uncertainty in Risk Governance
43(3)
Conclusion
46(7)
PART 2 METHODS AND CASE STUDIES OF RISK-BASED POLICING
5 The Theory of Risky Places
53(10)
Introduction
53(1)
Theories Relevant to Risk-Based Policing
54(8)
Conclusion
62(1)
6 High-Risk Target Areas and Priority Places
63(8)
Introduction
63(1)
Studying Exposure and Vulnerability to Crime
64(1)
Brooklyn as a Case Study
65(5)
Conclusion
70(1)
7 The Role of Police in Risk-Based Policing: Case Studies of Colorado Springs, Clendale, Newark, and Kansas City
71(31)
Introduction
71(1)
Risk Assessment Methodology
72(4)
Findings
76(22)
Connecting Risk Assessments to Intervention
98(2)
Conclusion
100(2)
8 Facilitators and Impediments to Designing, Implementing, and Evaluating Risk-Based Policing Strategies: Insights from Completed Researcher-Practitioner Partnerships
102(16)
Introduction
102(1)
Researcher-Practitioner Partnerships
103(1)
Planned Change and Program Implementation
104(2)
Risk-Based Policing Partnerships
106(1)
Findings
107(8)
Conclusion
115(3)
9 The Roles of Multiple Stakeholders in Risk-Based Policing: Case Studies of Jersey City and Atlantic City
118(8)
Introduction
118(1)
ACTION Meetings in Jersey City
119(1)
Risk-Based Policing in Atlantic City
120(4)
Conclusion
124(2)
10 People Make Risk-Based Policing and Data Actionable
126(7)
Valuing Data: Lessons Learned
126(2)
Beyond Training and into Active Problem Solving
128(3)
Conclusion
131(2)
Epilogue 133(4)
References 137(12)
Index 149
Leslie W. Kennedy is University Professor of Criminal Justice at Rutgers University and Director of the Rutgers Center on Public Security.

Joel M. Caplan is Associate Professor at Rutgers Universitys School of Criminal Justice and Deputy Director of the Rutgers Center on Public Security. He has professional experience as a police officer, 9-1-1 dispatcher, and emergency medical technician.

Eric L. Piza is Associate Professor at John Jay College of Criminal Justice, City University of New York. Prior to joining academia, he served as the Geographic Information Systems Specialist for the Newark Police Department in New Jersey.
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