Criminologist and politicians have debated the effectiveness of correctional rehabilitation programs since the 1970’s when criminal justice scholars and policy makers throughout the United States embraced Robert Martinson’s credo of “nothing works” (Shrum, 2004). Recidivism, the rate at which released offenders return to jail or prison, has become the most accepted outcome measure in corrections. The public's desire to reduce the economic and social costs associated with crime and incarceration has resulted in an emphasis on recidivism as an outcome measure of program effectiveness. While correctional facilities continue to grow, corrections make up an increasing amount of state and federal budgets. The recidivism rate in the United States is quite high, while the cost to taxpayers continues to increase. For legislatures, recidivism has become the primary outcome measure.
Assessing an offender’s risk to recidivate upon release from prison is one of the most important functions of a correctional organization (Brown et. al, 2009). Manchak et. al (2008) stated that the assessment of an individual’s risk for future criminal behavior is a routine part of practice in prisons and other correctional settings. Everyday correctional administrators must assess risk to inform important decisions about placing, managing, supervising, and treating offenders. This task has become more challenging as the size of the correctional population has burgeoned and the length of sentences has stretched (Manchak et. al, 2008). Additional time serve in prison has little impact on recidivism (Shrum, 2004). Measuring recidivism requires planning and commitment from correctional administrators. It also requires extensive follow up efforts from administrators, as well as, devoting resources to individual offenders who are no longer being served by a particular correctional facility. There are many factors that contribute to the rate of recidivism, such as poverty,
References: Anonymous (2005). Program said to reduce recidivism 33%. Corrections Forum, 14 (1), 15. Brown, S. L., St. Amand, M. D. & Zamble, E. (2009). The dynamic prediction of criminal recidivism: A three-wave prospective study Curtis, D. (2003). Panel IV: Accomplishing the purpose of sentencing-criminal history and recidivism Douglas, K. S., Epstein, M. E. & Poythress, N. G. (2008). Criminal recidivism among juvenile offenders: Testing the incremental and predictive validity of three measures of Jones, M. (2004). Maslow’s hierarchy of needs can lower recidivism. Corrections Today, 66 (4), 18-21. Manchak, S. M., Skeen, J. L. & Douglas, K. S. (2008). Utility of the revised Level of Service Inventory (LSI-R) in predicting recidivism after long-term incarceration Nimon, R. W. & Purcell, T. E. (2008). Recidivism: A time series analysis of navy releases, 1997-2003. Shrum, H. (2004). No longer theory: Correctional practices that work. Journal of Correctional Education, 55 (3), 225-236. Vacca, J. S. (2004). Educated prisoners are less likely to return to prison. Journal of Correctional Education, 55 (4), 297-306. Withrow, B. (2002). Evaluating rehabilitation programs with the Solomon Model. Corrections Compendium, 27 (10), 1-8.