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

Author:   Leslie W. Kennedy ,  Joel M. Caplan ,  Eric L. Piza
Publisher:   University of California Press
ISBN:  

9780520295636


Pages:   168
Publication Date:   20 November 2018
Format:   Paperback
Availability:   Out of stock   Availability explained
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Risk-Based Policing: Evidence-Based Crime Prevention with Big Data and Spatial Analytics


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Overview

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.

Full Product Details

Author:   Leslie W. Kennedy ,  Joel M. Caplan ,  Eric L. Piza
Publisher:   University of California Press
Imprint:   University of California Press
Dimensions:   Width: 17.80cm , Height: 1.50cm , Length: 25.40cm
Weight:   0.363kg
ISBN:  

9780520295636


ISBN 10:   0520295633
Pages:   168
Publication Date:   20 November 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface Acknowledgments PART 1: THE BASIC PRINCIPLES OF RISK-BASED POLICING 1. Introduction to Risk and Big Data Introduction to Risk-Based Policing in Crime Prevention The Importance of Risk Big Data Risk-Based Policing Conclusion 2. The Evolution of Modern Policing Introduction Police Reform and Professionalization From Professionalism to Problem-Solving The Importance of Places and Data Analysis in Contemporary Policing Conclusion 3. Policing in the New Era of Public Safety and Law Enforcement Focus on Places with Risk Terrain Modeling The Central Tenets of Risk-Based Policing Develop Spatial Risk Narratives Solicit and Value Input from Multiple Stakeholders Make Data-Driven Decisions Balance Strategies for Crime Risk Reduction Conclusion 4. Risk-Based Policing and ACTION Introduction Risk Governance and the Police Leader ACTION Meetings A Detailed Breakdown of the ACTION Agenda The Uncertainty in Risk Governance Conclusion PART 2: METHODS AND CASE STUDIES OF RISK-BASED POLICING 5. The Theory of Risky Places Introduction Theories Relevant to Risk-Based Policing Conclusion 6. High-Risk Target Areas and Priority Places Introduction Studying Exposure and Vulnerability to Crime Brooklyn as a Case Study Conclusion 7. The Role of Police in Risk-Based Policing: Case Studies of Colorado Springs, Glendale, Newark, and Kansas City Introduction Risk Assessment Methodology Findings Connecting Risk Assessments to Intervention Conclusion 8. Facilitators and Impediments to Designing, Implementing, and Evaluating Risk-Based Policing Strategies: Insights from Completed Researcher–Practitioner Partnerships Introduction Researcher–Practitioner Partnerships Planned Change and Program Implementation Risk-Based Policing Partnerships Findings Conclusion 9. The Roles of Multiple Stakeholders in Risk-Based Policing: Case Studies of Jersey City and Atlantic City Introduction ACTION Meetings in Jersey City Risk-Based Policing in Atlantic City Conclusion 10. People Make Risk-Based Policing and Data Actionable Valuing Data: Lessons Learned Beyond Training and into Active Problem Solving Conclusion Epilogue References Index

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Author Information

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 University’s 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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