Evidence-Based Offender Profiling of Serial Sex Worker Victim Homicides View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-11-11

AUTHORS

C. Gabrielle Salfati, Marina Sorochinski

ABSTRACT

Three general interlinked areas have been the focus of offender profiling research: individual differentiation (establishing differences between the behavioral actions of crime scene types), behavioral consistency (understanding behavioral patterns across a series of crimes), and offender profiling (linking sub-types of crime scene patterns to the most likely characteristics of an offender). Taken together, these three areas form the empirical basis necessary for use in criminal investigations. However, studies supporting inferences about offender characteristics have to date been the least developed in the field of offender profiling. For profiling to be fully useful to investigations, a clear understanding of three main elements is crucial to fully develop, notably (1) what individual crime scene characteristics are the most salient to use; (2) what elements of the full series behavioral developmental pattern are important to understand as an additional factor; and (3) what offender characteristics are the most empirically robust to focus on for investigative use. The current study examines 80 series of serial homicide, involving 302 crime scenes. Using the key elements of an offender’s crime scene behavioral patterns shown to help link and differentiate crime scenes and series, the current study linked these to sub-sets of different offender characteristics, identified as most useful for investigations. These included such characteristics such as age at the start of the series, criminal history specialization, general history of violence, mental health history, and relationship to the victims in the series. Results are discussed in the context of implications for research and practical applications in serial crime investigation and offender profiling. More... »

PAGES

679-690

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11896-021-09490-7

DOI

http://dx.doi.org/10.1007/s11896-021-09490-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1142514128


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