While serial killings have been the focus of much scholarly research, the definition of what it means to be a serial killer has been debated by law enforcement agencies and academics for decades. This overall lack of understanding about serial killers and the murders they commit has contributed to the numerous limitations concerning the general knowledge about this unique form of homicide. Furthermore, serial killers have typically been examined using psychological models, psychiatric approaches, or the external drives/motives of the offenders, while the development of a sociological perspective has received less attention. This current research uses arguably the most complete dataset on serial killings, the Radford database, to fill several gaps in the current body of knowledge by empirically analyzing 1,258 serial killers operating between 1985 and 2016. Data related to the killings, offenders, and victims, in addition to social structural variables, are examined to evaluate how these factors, among others, may possibly be associated with the number of victims an offender killed. Analyzing past definitions and research, this study expands sociological models examining serial murder, and contributes valuable insight into some of the myths and misunderstandings surrounding the crime, and how they likely lead to linkage blindness and decreased homicide clearance rates. Most importantly, this study provides an updated and improved understanding of serial killings that has the potential to be a tool for law enforcement professionals to increase the identity of potential offenders, can ultimately aid their efforts to address sociological origins of serial killing behaviors and attempt to prevent them in the future.
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Doctor of Philosophy (Ph.D.)
College of Sciences
Length of Campus-only Access
Doctoral Dissertation (Open Access)
Vincent, Jolene, "Serial Murder Mysteries: Revisiting Definitional Issues, Data Challenges, Archaic Theories, and Myths Using Empirical Evidence" (2018). Electronic Theses and Dissertations. 6439.
Restricted to the UCF community until February 2022; it will then be open access.