The Resource Predictive policing : the role of crime forecasting in law enforcement operations, Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood

Predictive policing : the role of crime forecasting in law enforcement operations, Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood

Label
Predictive policing : the role of crime forecasting in law enforcement operations
Title
Predictive policing
Title remainder
the role of crime forecasting in law enforcement operations
Statement of responsibility
Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood
Creator
Contributor
Provider
Subject
Language
eng
Summary
Predictive policing is the use of analytical techniques to identify targets for police intervention with the goal of preventing crime, solving past crimes, or identifying potential offenders and victims. These tools are not a substitute for integrated approaches to policing, nor are they a crystal ball. This guide assesses some of the most promising technical tools and tactical approaches for acting on predictions in an effective way
Cataloging source
DLC
http://library.link/vocab/creatorName
Perry, Walt L
Index
no index present
LC call number
HV7432
LC item number
.P47 2013
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
JSTOR Open Access
http://library.link/vocab/subjectName
  • Crime forecasting
  • Crime prevention
  • Criminal behavior, Prediction of
  • Police
  • BUSINESS & ECONOMICS
  • SOCIAL SCIENCE
  • LAW
  • Crime forecasting
  • Crime prevention
  • Criminal behavior, Prediction of
  • Police
  • United States
Label
Predictive policing : the role of crime forecasting in law enforcement operations, Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood
Instantiates
Publication
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Cover; Title Page; Copyright; Preface; Contents; Figures; Tables; Summary; Acknowledgments; Abbreviations; CHAPTER ONE: Introduction; What Is Predictive Policing?; A Criminological Justification for Predictive Policing: Why Crime Is "Predictable"; A Brief History of Predictive Policing; Background; Training; Study Objectives and Methods; Objectives; Approach; The Nature of Predictive Policing: This Is Not Minority Report; A Taxonomy of Predictive Methods; Prediction-Led Policing Processes and Practices; Data Collection; Analysis; Police Operations; Criminal Response; About This Report
  • CHAPTER TWO: Making Predictions About Potential CrimesNotes on Software; Hot Spot Analysis and Crime Mapping; Grid Mapping; Covering Ellipses; Single and Dual Kernel Density Estimation; Heuristic Methods; Regression Methods; Types of Relationships; Selecting Input Variables; Leading Indicators in Regression (and Other) Models; A Regression Example; Data Mining (Predictive Analytics); Clustering; Classification; Training and Testing a Model; Near-Repeat Methods; Spatiotemporal Analysis; Basics of Spatiotemporal Analysis; Heat Maps; Spatiotemporal Modeling Using the Generalized Additive Model
  • SeasonalityRisk Terrain Analysis; A Heuristic Approach: Risk Terrain Modeling; A Statistical Approach to Risk Terrain Analysis; Discussion of Risk Terrain Analysis Approaches; Prediction Methods; CHAPTER THREE: Using Predictions to Support Police Operations; Evidence-Based Policing; Taking Action on Hot Spots in Washington, D.C.; Koper Curve Application in Sacramento; Investigating Convenience Store Robberies in Chula Vista, California; Predictive Policing in Context: Case Studies; Shreveport, Louisiana: Predictive Intelligence-Led Operational Targeting
  • Memphis, Tennessee: Crime Reduction Utilizing Statistical HistoryNashville, Tennessee: Integrating Crime and Traffic Crash Data; Baltimore, Maryland: Crash-Crime Project; Iraq: Locating IED Emplacement Locations; Minneapolis, Minnesota: Micro Crime Hot Spots; Charlotte-Mecklenburg County, North Carolina: Foreclosures and Crime; Crime Maps: Community Relations; Police Actions; CHAPTER FOUR: Using Predictions to Support Investigations of Potential Offenders; Protecting Privacy Rights and Civil Liberties; Predictive Policing Symposium Assessment
  • Privacy Under the Fourth Amendment of the U.S. ConstitutionPrivacy with Respect to Policing Intelligence Information Systems; Privacy Resources for the Law Enforcement Community; Dealing with Noisy and Conflicting Data: Data Fusion; Heuristic and Simple-Model Methods; More Sophisticated Fusion Methods; Risk Assessment for Individual Criminal Behavior; Commonly Used Behavioral Instruments; Limitations of Behavioral Instruments; Quebec, Canada: Assessing Criminogenic Risks of Gang Members; Pittsburgh, Pennsylvania: Predicting Violence and Homicide Among Young Men
Extent
1 online resource (xxix, 155 pages)
Form of item
online
Isbn
9780833081551
Lccn
2013038720
Media category
computer
Media MARC source
rdamedia
Media type code
c
Specific material designation
remote
Stock number
22573/ctt487fgt
System control number
  • (OCoLC)858914485
  • (OCoLC)ocn858914485
Label
Predictive policing : the role of crime forecasting in law enforcement operations, Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood
Publication
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Cover; Title Page; Copyright; Preface; Contents; Figures; Tables; Summary; Acknowledgments; Abbreviations; CHAPTER ONE: Introduction; What Is Predictive Policing?; A Criminological Justification for Predictive Policing: Why Crime Is "Predictable"; A Brief History of Predictive Policing; Background; Training; Study Objectives and Methods; Objectives; Approach; The Nature of Predictive Policing: This Is Not Minority Report; A Taxonomy of Predictive Methods; Prediction-Led Policing Processes and Practices; Data Collection; Analysis; Police Operations; Criminal Response; About This Report
  • CHAPTER TWO: Making Predictions About Potential CrimesNotes on Software; Hot Spot Analysis and Crime Mapping; Grid Mapping; Covering Ellipses; Single and Dual Kernel Density Estimation; Heuristic Methods; Regression Methods; Types of Relationships; Selecting Input Variables; Leading Indicators in Regression (and Other) Models; A Regression Example; Data Mining (Predictive Analytics); Clustering; Classification; Training and Testing a Model; Near-Repeat Methods; Spatiotemporal Analysis; Basics of Spatiotemporal Analysis; Heat Maps; Spatiotemporal Modeling Using the Generalized Additive Model
  • SeasonalityRisk Terrain Analysis; A Heuristic Approach: Risk Terrain Modeling; A Statistical Approach to Risk Terrain Analysis; Discussion of Risk Terrain Analysis Approaches; Prediction Methods; CHAPTER THREE: Using Predictions to Support Police Operations; Evidence-Based Policing; Taking Action on Hot Spots in Washington, D.C.; Koper Curve Application in Sacramento; Investigating Convenience Store Robberies in Chula Vista, California; Predictive Policing in Context: Case Studies; Shreveport, Louisiana: Predictive Intelligence-Led Operational Targeting
  • Memphis, Tennessee: Crime Reduction Utilizing Statistical HistoryNashville, Tennessee: Integrating Crime and Traffic Crash Data; Baltimore, Maryland: Crash-Crime Project; Iraq: Locating IED Emplacement Locations; Minneapolis, Minnesota: Micro Crime Hot Spots; Charlotte-Mecklenburg County, North Carolina: Foreclosures and Crime; Crime Maps: Community Relations; Police Actions; CHAPTER FOUR: Using Predictions to Support Investigations of Potential Offenders; Protecting Privacy Rights and Civil Liberties; Predictive Policing Symposium Assessment
  • Privacy Under the Fourth Amendment of the U.S. ConstitutionPrivacy with Respect to Policing Intelligence Information Systems; Privacy Resources for the Law Enforcement Community; Dealing with Noisy and Conflicting Data: Data Fusion; Heuristic and Simple-Model Methods; More Sophisticated Fusion Methods; Risk Assessment for Individual Criminal Behavior; Commonly Used Behavioral Instruments; Limitations of Behavioral Instruments; Quebec, Canada: Assessing Criminogenic Risks of Gang Members; Pittsburgh, Pennsylvania: Predicting Violence and Homicide Among Young Men
Extent
1 online resource (xxix, 155 pages)
Form of item
online
Isbn
9780833081551
Lccn
2013038720
Media category
computer
Media MARC source
rdamedia
Media type code
c
Specific material designation
remote
Stock number
22573/ctt487fgt
System control number
  • (OCoLC)858914485
  • (OCoLC)ocn858914485

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