• Richard Berk


All of the material to this point would be at best academic if modern algorithmic risk forecasts were unable to inform practice. This chapter turns briefly to porting new forecasting procedures to the settings in which they will be used. There are technical issues, but often the major obstacles are interpersonal and organizational. Implementation can be the most challenging and time consuming step that must be anticipated as the risk algorithm is being developed.


  1. Berk, R. A. (2016) Statistical Learning from a Regression Perspective second edition New York: Springer.CrossRefGoogle Scholar
  2. Berk, R. A., Barnes, G., Ahlman, L. & Kurtz, E. (2010) When a second best is good enough: a comparison between a true experiment and a regression discontinuity quasi-experiment. journal of Experimental Criminology 6(2) 217–236.CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Richard Berk
    • 1
  1. 1.Department of CriminologyUniversity of PennsylvaniaPhiladelphiaUSA

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