Abstract
The objective of this study is to help investigators identify the characteristics of pickpocketing cases that are related to their solvability and detection and to use them to develop a predictive model for guiding case-screening decisions. It is based on a population of 36,260 pickpocketing incidents that took place on railway property policed by the British Transport Police between 2010 and 2015. Ten solvability factors were identified that explained 44% of the variation in detection outcomes and were used to calculate a solvability score for each incident, which indicates whether or not cases should be screened in for further investigation. The predictive model is five times as accurate as existing screening practices and can be used to discriminate between highly solvable cases likely to be detected and low-solvability cases with poor prospects of being solved. The use of a case-screening tool based on this predictive model could, depending on the solvability threshold selected, result in 30% rather than 90% of unsolved cases being investigated, saving over 20,000 h of investigation time a year wasted investigating difficult, if not impossible, to solve cases. A small number of cases that are currently solved would, with statistical case screening, remain undetected.
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Sharp, S., Coupe, R.T. (2019). Pickpocketing on Railways. In: Coupe, R., Ariel, B., Mueller-Johnson, K. (eds) Crime Solvability Factors. Springer, Cham. https://doi.org/10.1007/978-3-030-17160-5_6
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DOI: https://doi.org/10.1007/978-3-030-17160-5_6
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