Details

Subject(s)

• Community policing [Browse]
• Criminal justice, Administration of. [Browse]

Related name

• ProQuest (Firm) [Browse]

Series

Routledge series on practical and evidence-based policing

Biographical/​Historical note

Renée J. Mitchell served in the Sacramento Police Department for twenty-two years and is currently a Senior Police Researcher with RTI International. She holds a B.S. in Psychology, a M.A. in Counseling Psychology, a M.B.A., a J.D., and a Ph.D. in Criminology from the University of Cambridge. She has taught and lectured internationally on evidence-based policing and is best known for being the first policing pracademic to run a randomized controlled trial. She was a Fulbright Police Research Fellow and is the co-founder and executive committee member of the American Society of Evidence-Based Policing. She has two TEDx talks, "Research Not Protests" and "Policing Needs to Change: Trust me I'm a Cop," where she advocates for evidence-based policing. She has published her research in the Journal of Experimental Criminology, Justice Quarterly, and the Cambridge Journal of Evidence-Based Policing. Her books include Evidence Based Policing: An introduction and Implementing Evidence-Based Research: A How-to Guide for Police Organizations.

Summary note

"This book goes beyond other police leadership books to teach practitioners how to think about policing in a structured way that synthesizes criminological theory, statistics, research design, applied research, and what works and what doesn't in policing into Mental Models. A Mental Model is a representation of how something works. Using a Mental Model framework to simplify complex concepts, readers will take away an in-depth understanding of how cognitive biases affect our ability to understand and interpret data, how crime manifests itself in society, what empirical research says about effective police interventions, how statistical data should be used in management meetings, and how to evaluate interventions for efficiency and effectiveness. While evidence-based practice is critical to advancing the police profession, it is limited in scope, and is only part of what is necessary to support sustainable change in policing. Policing requires a scientifically based framework to understand and interpret data in a way that minimizes cognitive bias to allow for better responses to complex problems. Data and research have advanced so rapidly in the last several decades that it is difficult for even the most ambitious of police leaders to keep pace. The twenty-one Mental Models were synthesized to create a framework for any police, public, or community leader to better understand how cognitive bias contributes to misunderstanding data and how to overcome those biases to better serve your communities by reducing harm to your communities. The book is intended for a wide range of audiences, including law enforcement and community leaders; scholars and policy experts who specialize in policing; students of criminal justice, organizations, and management; reporters and journalists; individuals who aspire to police careers; and citizen consumers of information about policing. Anyone who is going to make decisions about their communities based on data, has a responsibility to be numerate. Twenty-one Mental Models That Can Change Policing will help you become just that"-- Provided by publisher.

Bibliographic references

Includes bibliographical references and index.

Reproduction note

Electronic reproduction. Ann Arbor, MI Available via World Wide Web.

Source of description

Description based on online resource; title from digital title page (viewed on October 19, 2021).

ISBN

• 9780367481520 (electronic book)
• 0367481529 (electronic book)
• 9781000402728 (electronic book)
• 100040272X (electronic book)
• 9781000402759 (electronic book)
• 1000402754 (electronic book)

LCCN

2021009174

OCLC

1245248323

Statement on language in description

Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage. Read more...