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16 Criminology & Pub. Pol'y 281 (2017)
Automated Offender Risk Assessment

handle is hein.journals/crpp16 and id is 283 raw text is: 




                         POLICY ESSAY

        RECIDIVISM RISK ASSESSMENT




Automated Offender Risk Assessment

The   Next   Generation or a Black Hole?


J. Stephen Wormith
University   of Soskatchewan



   he offender risk assessment enterprise   has been moving at warp speed since the
         turn of the millennium and shows no signs of slowing. This is good. It reflects the
         importance of offender risk assessment in the field of criminal justice, as well as the
energy, thought, and creativity that is being invested in efforts to build a better mousetrap.
It is a vibrant and robust area of research that has a direct application to correctional policy
and practice in numerous ways. Nevertheless, the development of offender risk assessment
began long before the many developments of this modern era. This review describes how
the recently constructed Minnesota Screening Tool Assessing Recidivism Risk (MnSTARR,
2.0), and its related research by Grant Duwe and Michael Rocque (2017, this issue) in
Minnesota, represent a culmination of this history and points out some questions that the
scale's implementation has for policy and practice.


Offender Risk Assessment Generations and Other Variations
Bonta (1996) documented  the early offender risk assessment innovations in what he de-
scribed as a series of progressions or generations beginning with traditional clinical judg-
ment  (first generation), followed by the movement to actuarial assessments that were based
on static risk factors (second generation), and then by assessments of risk and (dynamic)
criminogenic need factors (third generation), which generate not only an assessment of
offender risk but also give direction for clinicians and correctional staff to pursue in their
work with offenders. By the turn of the century, the results of meta-analyses convincingly
established the superiority of mechanical (second and third generation) over subjective (first
generation) predictions of human behavior in numerous disciplines, but the differences


Disclosure: J. Stephen Wormith receives royalty payments for the Level of Service/Case Management
Inventory from its publisher, Multi-Health Systems, Toronto, Canada. Direct correspondence to J. Stephen
Wormith, Department of Psychology, 9 Campus Drive, University of Saskatchewan, Saskatoon SK, Canada, 57N
5A5 (e-mail: s.wormith@usask.ca).

DOI:10. 1111/1745-9133.12277             Q 2017 American Society of Criminology 281
                                  Criminology & Public Policy * Volume 16 * Issue 1

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