Predictive policing (Record no. 393318)

001 - ETIQUETA DE REGISTO
Identificador do registo 393318
010 ## - NÚMERO INTERNACIONAL NORMALIZADO DOS LIVROS (ISBN)
Número (ISBN) 9780833081483
100 ## - DADOS GERAIS DE PROCESSAMENTO
Dados gerais de processamento 20150608d2013 y0pory50 ba
101 ## - LÍNGUA DA PUBLICAÇÃO
Língua do texto, banda sonora, etc. Inglês
200 ## - TÍTULO E MENÇÃO DE RESPONSABILIDADE
Título próprio Predictive policing
Indicação genérica do tipo de material Recurso eletrónico
Informação de outro título the role of crime forecasting in law enforcement operations
Primeira menção de responsabilidade Walter L. Perry ...[et al.].
210 ## - PUBLICAÇÃO, DISTRIBUIÇÃO, ETC.
Lugar da publicação, distribuição, etc. Santa Monica
Nome do editor, distribuidor, etc. RAND Corporation
Data da publicação, distribuição, etc. 2013
215 ## - DESCRIÇÃO FÍSICA
Indicação específica do tipo de material e extensão do item 1 CD-ROM
Dimensões 12 cm
225 ## - COLECÇÃO
Título próprio da colecção Safety And Justice Program
300 ## - NOTAS GERAIS
Texto da nota The research described in this report was sponsored by the National Institute of Justice and conducted in the Safety and Justice Program within RAND Justice, Infrastructure, and Environment.
330 ## - SÚMULA OU RESUMO
Texto da nota Preface. Figures. Tables. Summary. Acknowledgments. Abbreviations. Chapt er 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 crimes. Notes 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. Seasonality. Risk 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 history. Nashville, 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. Constitution. Privacy 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. Risk assessment for organized crime behavior. Risk assessment instruments for domestic violence. Risk assessment instruments for mental health. Predictive methods: finding suspects. Basic queries. Criminal intelligence in social network analysis format. Links to Department of Motor Vehicle Registries, Pawn Data, and other registries. Anchor point analysis, or geographic profiling. Modus Operandi similarity analysis. Exploitation of sensor data. Putting the clues together: multisystem and network queries. Taking action on predictions. Identifying high-risk individuals. Identifying the most likely suspects. Prediction-based offender intervention in context. Florida State Department of Juvenile Justice: preemptive efforts. Predicting predator hunting patterns. Chapter Five. Findings for practitioners, developers, and policymakers. Predictive policing myths. Myth 1: The computer actually knows the future. Myth 2: The computer will do everything for you. Myth 3: you need a high-powered (and expensive) model. Myth 4: Accurate predictions automatically lead to major crime reductions. Predictive policing pitfalls. Pitfall 1: Focusing on prediction accuracy instead of tactical utility. Pitfall 2: Relying on poor-quality data. Pitfall 3: Misunderstanding the factors behind the prediction. Pitfall 4: Underemphasizing assessment and evaluation. Pitfall 5: Overlooking civil and privacy rights. A Buyer's Guide to Predictive Policing. A Developer’s Guide to Predictive Policing. Desired capabilities. Controlling the hype. Access and affordability. A Crime Fighter’s Guide to using Predictive Policing: emerging practices. Supporting the establishment of predictive policing processes. Practices for data collection and analysis: creating shared situational awareness. Operations: Key sources of information on interventions. Promising general practices for operations.. Conclusions. About the authors. Bibliography.
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada GEOGRAFIA CRIMINAL
ID Autoridade 329853
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada MAPEAMENTO DO CRIME
ID Autoridade 343998
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada ANÁLISE CRIMINAL
ID Autoridade 321724
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada SISTEMA DE INFORMAÇÃO GEOGRÁFICA
ID Autoridade 344179
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada INFORMAÇÃO COMPUTORIZADA
ID Autoridade 343610
606 ## - NOME COMUM USADO COMO ASSUNTO
Elemento de entrada ESTADOS UNIDOS
ID Autoridade 334103
710 ## - NOME DE COLECTIVIDADE - RESPONSABILIDADE PRINCIPAL
Palavra de ordem PREDICTIVE POLICING
ID Autoridade 357750
955 ## -
-- Oferta
995 ## - LOCALIZAÇÃO E INFORMAÇÃO DE EXEMPLARES
-- 0
-- PJCD_258_000000000000000
-- 2022-06-06
-- 2022-06-06
-- 0
Holdings
Número de registo Número interno Koha (auto-gerado) Biblioteca de aquisição Biblioteca de empréstimo Código de barras Cota Tipo de documento Forma de aquisição
PJCD258 425764 Biblioteca da Polícia Judiciária Biblioteca da Polícia Judiciária PJ1CD258_63 PJCD258 Monografias Oferta