caa a22 4500 463170822 CHVBK 20180406164812.0 cr unu---uuuuu 170326e20071201xx s 000 0 eng 10.1007/s10940-007-9035-1 doi (NATIONALLICENCE)springer-10.1007/s10940-007-9035-1 Sentencing Using Statistical Treatment Rules: What We Don't Know Can Hurt Us [Elektronische Daten] [Shawn Bushway, Jeffrey Smith] The existing literature seriously misinterprets the available evidence on the predictability of high rate criminal offending and thus the potential value of statistical treatment rules that impose stiffer punishments on offenders with higher predicted risk of recidivism. The misinterpretation results from the failure to take account of the fact that the data used in existing risk assessment exercises come from environments characterized by informal (and sometimes formal) attempts by judges and other actors to base penal treatments on expected recidivism. Findings of little or no predictive power for baseline covariates may simply indicate the efficient use of the available information. We lay out the problem in detail, provide examples from several literatures and then consider general solutions to the problem. Springer Science+Business Media, LLC, 2007 Selective incarceration nationallicence Sentencing nationallicence Statistical treatment rule nationallicence Profiling nationallicence Bushway Shawn School of Criminal Justice, University at Albany, 135 Western Avenue, 219 Draper Hall, 12222, Albany, NY, USA aut Smith Jeffrey Department of Economics, University of Michigan, 238 Lorch Hall, 611 Tappan Street, 48109-1220, Ann Arbor, MI, USA aut Journal of Quantitative Criminology Springer US; http://www.springer-ny.com 23/4(2007-12-01), 377-387 0748-4518 23:4<377 2007 23 10940 https://doi.org/10.1007/s10940-007-9035-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10940-007-9035-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bushway Shawn School of Criminal Justice, University at Albany, 135 Western Avenue, 219 Draper Hall, 12222, Albany, NY, USA aut NATIONALLICENCE 700 1- Smith Jeffrey Department of Economics, University of Michigan, 238 Lorch Hall, 611 Tappan Street, 48109-1220, Ann Arbor, MI, USA aut NATIONALLICENCE 773 0- Journal of Quantitative Criminology Springer US; http://www.springer-ny.com 23/4(2007-12-01), 377-387 0748-4518 23:4<377 2007 23 10940 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer