Revisiting prediction models in policing: Identifying high-risk offenders
The use of prediction models for classifying offenders has been a common practice by the criminal justice system. Given the recent developments in criminal career research and continuing evidence that a small proportion of chronic offenders are responsible for the majority of crime, there is a conti...
| Autor principal: | |
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| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2006
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| En: |
American journal of criminal justice
Año: 2006, Volumen: 31, Número: 1, Páginas: 35-50 |
| Acceso en línea: |
Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | The use of prediction models for classifying offenders has been a common practice by the criminal justice system. Given the recent developments in criminal career research and continuing evidence that a small proportion of chronic offenders are responsible for the majority of crime, there is a continued need to identify high-risk offenders early on in their offending careers. The present study provides support for the accuracy of an innovative prediction instrument that was developed for identifying high-risk offenders in a rural county in a southern state. Offender risk classification was found to be associated with reoffending across different dimensions of assessment and the high-risk offenders had accumulated a greater mean number of arrests upon six-month follow-up when compared to the medium and low-risk offenders. Policy implications and directions for future research incorporating prediction models in policing are also discussed. |
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| ISSN: | 1936-1351 |
| DOI: | 10.1007/BF02885683 |