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An algorithmic strategy for measuring police presence with GPS data.

Robin KhalfaThom SnaphaanWim Hardyns
Published in: Crime science (2024)
This study introduces an algorithmic strategy for measuring dimensions of police presence at microgeographic units using GPS data from police patrol units. The proposed strategy builds upon the integrated theory of hot spots patrol strategy from Sherman et al. (Journal of Contemporary Criminal Justice 30:95-122, 2014), focusing on three key dimensions: the frequency, duration, and intermittency of police presence. This study provides pseudocodes for the algorithm, facilitating the pre-processing of GPS-derived data sequences to generate measures of these three central concepts. The measures presented in this article offer a framework for investigating the impact of police presence on crime and other relevant crime-related outcomes at microgeographic units, using GPS data. This algorithmic strategy may further contribute to the development of evidence-based strategies in place-based policing initiatives.
Keyphrases
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  • big data
  • machine learning
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  • artificial intelligence
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