NCJ Number
213865
Journal
European Journal of Criminology Volume: 3 Issue: 2 Dated: April 2006 Pages: 181-200
Date Published
April 2006
Length
20 pages
Annotation
This paper argues for diversity in evaluations of community corrections programs in the United Kingdom by identifying and assessing the various evaluation measures that have been and might be used; it questions the value of relying on reconviction rates as a measure of what works.
Abstract
Evaluations of community corrections programs should have pluralistic designs, which means they incorporate a range of indicators of effectiveness; an awareness of the organizational context of program development; a knowledge of the social context within which the program operates and how this affects offenders' opportunities and priorities; documentation of organizational inputs; and systemic identification of and responses to weaknesses. Few evaluations have been this comprehensive and diverse in their measurements. The most common measures of program effectiveness have involved analyses of recidivism rates or program costs. Other measures have focused on the diversion of offenders from custody, sentencer satisfaction, and changed attitudes of offenders. This paper argues that no single measure of a program's impact can reveal the full picture of what a correctional program has accomplished. The authors criticize current efforts to drive program design based on limited evaluation goals. Designing a program based only on evaluation concerns means the program is composed only of components and objectives that can be measured according to unimaginative and limited criteria. Programs must focus on particular identified needs of offenders determined to be central in causing and contributing directly and indirectly to their criminal behavior. Services should then be designed to address various facets of those needs. It is up to evaluators to then tailor their evaluation measures to the multiple impacts that the program has on offenders under varying conditions according to multiple variables. 100 references