Joel M. Caplan & Eric L. Piza 
Risk-Based Policing [PDF ebook] 
Evidence-Based Crime Prevention with Big Data and Spatial Analytics

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.

表中的内容

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

关于作者

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.