Predicting rapist type based on crime-scene violence, interpersonal involvement, and criminal sophistication in U.S. stranger rape cases
Stranger rape cases are one of the most difficult sexual assault crimes to solve for law enforcement. This study aimed to compare crime-scene characteristics between serial rapists and single-victim rapists in stranger rape cases and build a predictive model to predict rapist type. An archival datab...
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| Otros Autores: | ; |
| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2022
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| En: |
International journal of police science & management
Año: 2022, Volumen: 24, Número: 1, Páginas: 53-65 |
| Acceso en línea: |
Volltext (kostenfrei) |
| Journals Online & Print: | Gargar...
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | Stranger rape cases are one of the most difficult sexual assault crimes to solve for law enforcement. This study aimed to compare crime-scene characteristics between serial rapists and single-victim rapists in stranger rape cases and build a predictive model to predict rapist type. An archival database of released sex offenders included 385 who committed stranger rapes. Of those, 244 were single-victim rapists and 141 were serial rapists. The single-victim rapists were significantly more likely to have violently themed crime-scene characteristics than serial rapists, whereas serial rapists were significantly more likely than single-victim rapists to engage in criminally sophisticated behavior and induce participation from their victims. A logistic regression using 10 crime-scene characteristics correctly identified 75.8% of cases as perpetrated by either single-victim or serial rapists. The most significant predictors of rapist type were whether the offender digitally penetrated their victim, whether the offender choked their victim, whether they were at a new/unknown location or whether they threatened their victim. The implications of these results are that they benefit law enforcement in the investigation of stranger rape cases by potentially narrowing down their suspect pool and add to the classification of stranger rapists in offender profiling literature. |
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| ISSN: | 1478-1603 |
| DOI: | 10.1177/14613557211036564 |
