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The Indianapolis harmspot policing experiment

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Listed:
  • Carter, Jeremy G.
  • Mohler, George
  • Raje, Rajeev
  • Chowdhury, Nahida
  • Pandey, Saurabh

Abstract

This 100-day experiment explored the impact of a dynamic place-based policing strategy on social harm in Indianapolis. Scholars have recently called for place-based policing to consider the co-occurrence of substance abuse and mental health problems that correlate within crime hot spots. Moreover, severity is not ubiquitous across harmful events and should thus be weighted accordingly.

Suggested Citation

  • Carter, Jeremy G. & Mohler, George & Raje, Rajeev & Chowdhury, Nahida & Pandey, Saurabh, 2021. "The Indianapolis harmspot policing experiment," Journal of Criminal Justice, Elsevier, vol. 74(C).
  • Handle: RePEc:eee:jcjust:v:74:y:2021:i:c:s0047235221000349
    DOI: 10.1016/j.jcrimjus.2021.101814
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    References listed on IDEAS

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    1. Hunt, Priscillia Evelyne & Saunders, Jessica & Kilmer, Beau, 2019. "Estimates of Law Enforcement Costs by Crime Type for Benefit-Cost Analyses," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 10(1), pages 95-123, April.
    2. G. O. Mohler & M. B. Short & Sean Malinowski & Mark Johnson & G. E. Tita & Andrea L. Bertozzi & P. J. Brantingham, 2015. "Randomized Controlled Field Trials of Predictive Policing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1399-1411, December.
    3. Mohler, G. O. & Short, M. B. & Brantingham, P. J. & Schoenberg, F. P. & Tita, G. E., 2011. "Self-Exciting Point Process Modeling of Crime," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 100-108.
    4. Lersch, Kim M., 2020. "Exploring the geography of suicide threats and suicide attempts: An application of Risk Terrain Modeling," Social Science & Medicine, Elsevier, vol. 249(C).
    5. Lin, Chien-Yu & Hsu, Chia-Yueh & Gunnell, David & Chen, Ying-Yeh & Chang, Shu-Sen, 2019. "Spatial patterning, correlates, and inequality in suicide across 432 neighborhoods in Taipei City, Taiwan," Social Science & Medicine, Elsevier, vol. 222(C), pages 20-34.
    6. Rafael Prieto Curiel & Humberto González Ramírez & Steven Richard Bishop, 2018. "A novel rare event approach to measure the randomness and concentration of road accidents," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    7. Mohler, George & Carter, Jeremy & Raje, Rajeev, 2018. "Improving social harm indices with a modulated Hawkes process," International Journal of Forecasting, Elsevier, vol. 34(3), pages 431-439.
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    Cited by:

    1. Robin Khalfa & Wim Hardyns, 2024. "‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing," Evaluation Review, , vol. 48(5), pages 797-847, October.
    2. Perez, Yuri & Gonçalves, Luis Fernando & Pereira, Fabio Henrique, 2025. "An urban network percolation based spatiotemporal analysis of crime hotspot using directed acyclic graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 669(C).

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