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Killer Data examines the phenomenon of serial murder using data collected from international sources to review offender patterning with a focus on contemporary cases. This type of attention will allow for a broader understanding of modern-day serial murderers and will help to dispel some of the myths that surround offenders.
The current serial murder classification scheme incorrectly types serial murderers as supremely intelligent killing machines while discounting their socialization, experiences, and choices. This book exposes serial murderers as run-of-the-mill hometown losers, who brutalize women, and are lucky to escape apprehension. Like other atypical homicide offenders, modern-day serial murderers are propelled forward by a deep sense of entitlement, easy access to firearms, and a nonchalant attitude toward using murder to attain their goals. Readers should come away with a deeper understanding not of the ultra-rare or the "deadliest" serial murderers but of the more common offenders who pose a consistent threat to day-to-day life. The book utilizes the Consolidated Serial Homicide Offender Database, one of the largest and most robust open access databases of multiple murders available, presenting new thinking on areas such as:
These findings are illustrated with 200 narrative vignettes of serial murder series that occurred between 2011 and 2021, such as Itzcoatl Ocampo, Charles Severance, Nikko Jenkins, and Pamela Hupp, offenders who may be unfamiliar to many but represent the next iteration of the serial murderer.
Correcting decades of flawed assumptions about serial murderers, and written in an accessible and concise style, Killer Data is essential reading for students and scholars of criminal justice and criminology, law enforcement professionals, and the interested general reader.
