Taxonomic Discrimination Among Sex Offenders: Forensic Utility?

Lamade, Raina V.; Prentky, Robert A.

doi:10.1007/978-3-030-04696-5_4

Cited by 2 publications

(1 citation statement)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, a limitation of previous research is that they often use a sample of only convicted rapists. Due to the judicial difficulties involved in obtaining a conviction for sexual offences, convicted rapists may constitute a subset of offenders quite unrepresentative of the larger population of men who commit sexual offences (Lamade & Prentky, 2019). For this reason, this research has a larger sample of police reported cases of serial and one-off rapists and it includes not only a subset of rapists (convicted ones), but a larger sample of identified rapists, who may or may not be incarcerated for other reasons not related to their culpability.…”

Section: Current Studymentioning

confidence: 99%

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

Ramírez

Framis

Álvarez

et al. 2021

J Interpers Violence

View full text Add to dashboard Cite

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 crime-related variables was able to predict whether an unknown offender is a one-off 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.

show abstract

Section: Current Studymentioning

confidence: 99%