PublicadoEl 23/11/22 por Comillas
Artículo

Predicting Serial Stranger Rapists: Developing a Statistical Model From Crime Scene Behaviors

tipo de documento semantico ckh_publication

Ficheros

captura pantalla articulo seriales.png
Tamaño 833779
Formato image/png
Fecha de publicación 22/09/2021
Fuente Revista: Journal of Interpersonal Violence, Periodo: 1, Volumen: 37, Número: 19-20, Página inicial: 1, Página final: 19
Estado info:eu-repo/semantics/publishedVersion

Resumen

Idioma es-ES
Resumen

Stranger rapes are the most difficult cases to solve for the police, especially when a serial rapist is involved. Recent research in offender profiling has focused on generating inferences between crime scene variables and offender characteristics to aid the police investigation. This study aims to develop an empirical model to predict a new case of a serial stranger rapist by analyzing a Spanish sample of 231 one-off and 38 serial sexual offenders. A multivariate logistic regression model that included eight significant crimerelated variables was able to predict whether an unknown offender is a oneoff or serial rapist based only on the victim’s account. The predictive validity of the model was tested using receiver operating characteristic (ROC) analysis and the result of AUC value indicated a medium predictive capacity. The final model correctly classifies nearly 80% of serial stranger rapist cases. The implications of these findings for criminal investigation are discussed.

Idioma en-GB
Resumen

Stranger rapes are the most difficult cases to solve for the police, especially when a serial rapist is involved. Recent research in offender profiling has focused on generating inferences between crime scene variables and offender characteristics to aid the police investigation. This study aims to develop an empirical model to predict a new case of a serial stranger rapist by analyzing a Spanish sample of 231 one-off and 38 serial sexual offenders. A multivariate logistic regression model that included eight significant crimerelated variables was able to predict whether an unknown offender is a oneoff or serial rapist based only on the victim’s account. The predictive validity of the model was tested using receiver operating characteristic (ROC) analysis and the result of AUC value indicated a medium predictive capacity. The final model correctly classifies nearly 80% of serial stranger rapist cases. The implications of these findings for criminal investigation are discussed.

Uri identificador doi: 10.1177/08862605211044968
Grupos de investigación y líneas temáticas Derecho Penal y Criminología - Seguridad y Política Criminal

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Tipo de archivo image/png
Idioma es-ES
Tipo de acceso info:eu-repo/semantics/openAccess
Licencia http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Fecha de modificacion 26/09/2022
Fecha de disponibilidad 02/09/2021
fecha de alta 02/09/2021

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