Predictive policing :: the role of crime forecasting in law enforcement operations /
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 b...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Santa Monica, CA :
RAND,
[2013]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource (xxix, 155 pages) |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9780833081551 0833081551 |
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| 100 | 1 | |a Perry, Walt L. | |
| 245 | 1 | 0 | |a Predictive policing : |b the role of crime forecasting in law enforcement operations / |c Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood. |
| 264 | 1 | |a Santa Monica, CA : |b RAND, |c [2013] | |
| 300 | |a 1 online resource (xxix, 155 pages) | ||
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| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Print version record and CIP data provided by publisher; resource not viewed. | |
| 520 | |a 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. | ||
| 505 | 0 | |a Introduction -- Making predictions about potential crimes -- Using predictions to support police operations -- Using predictions to support investigations of potential offenders -- Findings for practitioners, developers, and policymakers. | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 650 | 0 | |a Crime forecasting |z United States. | |
| 650 | 0 | |a Crime prevention |z United States. | |
| 650 | 0 | |a Criminal behavior, Prediction of |z United States. | |
| 650 | 0 | |a Police |z United States. |0 http://id.loc.gov/authorities/subjects/sh85104208 | |
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| 650 | 7 | |a SOCIAL SCIENCE |x General. |2 bisacsh | |
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| 650 | 7 | |a Crime forecasting |2 fast | |
| 650 | 7 | |a Crime prevention |2 fast | |
| 650 | 7 | |a Criminal behavior, Prediction of |2 fast | |
| 650 | 7 | |a Police |2 fast | |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBU-ocn858914485 |
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| _version_ | 1816796911060910080 |
| adam_text | |
| any_adam_object | |
| author | Perry, Walt L. |
| author_facet | Perry, Walt L. |
| author_role | |
| author_sort | Perry, Walt L. |
| author_variant | w l p wl wlp |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
| callnumber-label | HV7432 |
| callnumber-raw | HV7432 .P47 2013 |
| callnumber-search | HV7432 .P47 2013 |
| callnumber-sort | HV 47432 P47 42013 |
| callnumber-subject | HV - Social Pathology, Criminology |
| collection | ZDB-4-EBU |
| contents | Introduction -- Making predictions about potential crimes -- Using predictions to support police operations -- Using predictions to support investigations of potential offenders -- Findings for practitioners, developers, and policymakers. 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. |
| ctrlnum | (OCoLC)858914485 |
| dewey-full | 363.23 |
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| dewey-ones | 363 - Other social problems and services |
| dewey-raw | 363.23 |
| dewey-search | 363.23 |
| dewey-sort | 3363.23 |
| dewey-tens | 360 - Social problems and services; associations |
| discipline | Soziologie |
| format | Electronic eBook |
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Perry, Brian McInnis, Carter C. Price, Susan C. Smith, John S. Hollywood.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Santa Monica, CA :</subfield><subfield code="b">RAND,</subfield><subfield code="c">[2013]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (xxix, 155 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references.</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Print version record and CIP data provided by publisher; resource not viewed.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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. 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Prediction-Led Policing Processes and Practices; Data Collection; Analysis; Police Operations; Criminal Response; About This Report.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">SeasonalityRisk Terrain Analysis; A Heuristic Approach: Risk Terrain Modeling; A Statistical Approach to 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| id | ZDB-4-EBU-ocn858914485 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:49:11Z |
| institution | BVB |
| isbn | 9780833081551 0833081551 |
| language | English |
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| spelling | Perry, Walt L. 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. Santa Monica, CA : RAND, [2013] 1 online resource (xxix, 155 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references. Print version record and CIP data provided by publisher; resource not viewed. 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. Introduction -- Making predictions about potential crimes -- Using predictions to support police operations -- Using predictions to support investigations of potential offenders -- Findings for practitioners, developers, and policymakers. 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. Crime forecasting United States. Crime prevention United States. Criminal behavior, Prediction of United States. Police United States. http://id.loc.gov/authorities/subjects/sh85104208 Criminalité Prévision États-Unis. BUSINESS & ECONOMICS Infrastructure. bisacsh SOCIAL SCIENCE General. bisacsh LAW Criminal Law General. bisacsh Crime forecasting fast Crime prevention fast Criminal behavior, Prediction of fast Police fast United States fast https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq has work: Predictive policing (Text) https://id.oclc.org/worldcat/entity/E39PCGTHHf8xpbBMP3rjVMBwqP https://id.oclc.org/worldcat/ontology/hasWork Books at JSTOR: Open Access JSTOR Print version: Perry, Walt L. Predictive policing. Santa Monica, CA : RAND, 2013 9780833081483 (DLC) 2013037754 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=646990 Volltext |
| spellingShingle | Perry, Walt L. Predictive policing : the role of crime forecasting in law enforcement operations / Introduction -- Making predictions about potential crimes -- Using predictions to support police operations -- Using predictions to support investigations of potential offenders -- Findings for practitioners, developers, and policymakers. 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. Crime forecasting United States. Crime prevention United States. Criminal behavior, Prediction of United States. Police United States. http://id.loc.gov/authorities/subjects/sh85104208 Criminalité Prévision États-Unis. BUSINESS & ECONOMICS Infrastructure. bisacsh SOCIAL SCIENCE General. bisacsh LAW Criminal Law General. bisacsh Crime forecasting fast Crime prevention fast Criminal behavior, Prediction of fast Police fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85104208 |
| title | Predictive policing : the role of crime forecasting in law enforcement operations / |
| title_auth | Predictive policing : the role of crime forecasting in law enforcement operations / |
| title_exact_search | Predictive policing : the role of crime forecasting in law enforcement operations / |
| title_full | 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. |
| title_fullStr | 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. |
| title_full_unstemmed | 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. |
| title_short | Predictive policing : |
| title_sort | predictive policing the role of crime forecasting in law enforcement operations |
| title_sub | the role of crime forecasting in law enforcement operations / |
| topic | Crime forecasting United States. Crime prevention United States. Criminal behavior, Prediction of United States. Police United States. http://id.loc.gov/authorities/subjects/sh85104208 Criminalité Prévision États-Unis. BUSINESS & ECONOMICS Infrastructure. bisacsh SOCIAL SCIENCE General. bisacsh LAW Criminal Law General. bisacsh Crime forecasting fast Crime prevention fast Criminal behavior, Prediction of fast Police fast |
| topic_facet | Crime forecasting United States. Crime prevention United States. Criminal behavior, Prediction of United States. Police United States. Criminalité Prévision États-Unis. BUSINESS & ECONOMICS Infrastructure. SOCIAL SCIENCE General. LAW Criminal Law General. Crime forecasting Crime prevention Criminal behavior, Prediction of Police United States |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=646990 |
| work_keys_str_mv | AT perrywaltl predictivepolicingtheroleofcrimeforecastinginlawenforcementoperations |