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Sage Research Methods Case 2: Using unobtrusive data to study criminal behavior: Understanding malicious contamination incidents

Sage Research Methods Case 2: Using unobtrusive data to study criminal behavior: Understanding malicious contamination incidents

Kilbane, Sarah C. (2018) Sage Research Methods Case 2: Using unobtrusive data to study criminal behavior: Understanding malicious contamination incidents. [Working Paper] (doi:https://doi.org/10.4135/9781526440556)

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Abstract

Malicious contamination is a term used to describe a number of different types of criminal activity, from poisoning and product tampering to extortion and food terrorism. However, little is known about these types of crime as few empirical studies have been conducted to date. In particular, there is a lack of clear definitions in the literature for terms like “product tampering” and “poisoning.” To develop such definitions and to explore crimes of malicious contamination in more depth, a database was constructed consisting of all known incidents of malicious contamination worldwide occurring over a 40-year period. Out of necessity, this database was constructed using unobtrusive, open source data which was then content analyzed for the presence or absence of pertinent behavioral variables. The following case study highlights the advantages and disadvantages of working with unobtrusive data to study criminal behavior, including issues related to validity, reliability, and credibility. Specific examples have been included from the author’s own PhD work and subsequent publication, with an emphasis on how some of the abovementioned challenges were addressed. The importance of unobtrusive data to the study of forensic and investigative psychology is also discussed.

Item Type: Working Paper
Uncontrolled Keywords: unobtrusive measures, criminal behaviour, malicious contamination
Subjects: K Law > K Law (General)
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Law
Faculty of Architecture, Computing & Humanities > Law & Criminology Research Group
Last Modified: 13 May 2019 13:12
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 4
URI: http://gala.gre.ac.uk/id/eprint/18576

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