Characteristics of Cause of Death, Victim, Crime, Offender, and Familial Relationship

• Main Author: Reilly, William J
• Format: Others
• Language: en
• Published: ScholarWorks 2019
• Subjects: Clandestine Grave; Criminal Profiling; Familial Relationship; Forensic Psychology; Method of Death; Spacial Distance; Social and Behavioral Sciences
• Online Access: https://scholarworks.waldenu.edu/dissertations/7726; https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=8998&context=dissertations

Broad personality or global traits are unlikely to assist in solving capital crimes, so forensic psychologists have begun to focus on characteristics of the crime to create differentiating profiles. The purpose of this study was to determine if offender and victim characteristics and method of murder could provide cluster profiles differentiating familial relationship between offender and victim. Guided by classical conditioning theory and social learning theory, an archival database of 147 capital offenders responsible for 506 victims was analyzed. Cluster analysis yielded 3 distinct profiles. Compared to other clusters, Cluster 1 offenders tended to be Black and unfamiliar with their victims, who tended to be male between 20 and 50 years old that were typically shot. Cluster 2 offenders tended to be White and familiar with their typically female victims under the age of 20 who they typically murdered by use of blunt force or strangulation. Cluster 3 offenders were distinguished from the other 2 clusters only by having accounted for 90.6% of all victims who were stabbed, but no other associations with variables in the data set were discovered to explain this finding. Though limited in sample size, range of variables, and supplemental insights that could have been gained from case files or interviews, the results contribute to positive social change with offender-victim characteristics and method of murder profiles that begin to differentiate the familial offender-victim relationship and that future research can prospectively build on to create retrospective profiling models, which could potentially lead to resolving unsolved serial murder cases.