The Rehabilitative Ideal versus the Criminogenic Reality: The Consequences of Warehousing Prisoners

ABSTRACT

Using data on more than 55,000 offenders released from Minnesota prisons, we examine whether criminogenic effects arising from imprisonment may stem from a lack of institutional programming. We also evaluate the impact of participation in multiple correctional interventions on recidivism. The results show 31 percent of the Minnesota prisoners were warehoused, which significantly increased the odds of recidivism by 13 percent. Participation in at least one successful recidivism-reduction intervention lowered the odds of recidivism by 12 percent, while involvement in two effective programs decreased it by 26 percent. We conclude by discussing the implications of warehousing, which was more likely to occur for prisoners with brief stays in prison who were admitted as probation or parole violators.

KEYWORDS:

• Recidivism
• prison
• correctional interventions
• warehousing
• criminogenic

Notes

1. Prison visitation has not always been considered a correctional intervention. Unlike most correctional programs, there is seldom a limit on the number of prisoners who can participate (i.e., receive visits). Moreover, in most instances, visitation is not a program with well-defined beginning and end points that offenders must complete. Nevertheless, we regard prison visitation as an intervention because it has been found to be associated with a reduction in recidivism (Bales & Mears, 2008; Cochran, 2014; Mears, Cochran, Siennick, & Bales, 2012), including Minnesota prisoners (Duwe & Clark, 2013; Duwe and Johnson, 2016). And prison visitation can provide offenders with pro-social support, which addresses anti-social peers—a major criminogenic need.

2. High-fidelity Moving On was delivered to female prisoners prior to 2011, and its operation was largely consistent with how the program was designed. Class sizes were relatively small (fewer than 10 participants), the program lasted at least 3 months, and participation was voluntary. On the other hand, when low-fidelity Moving On was offered from 2011 to 2013, it had large class sizes (more than 40 participants), the length of the program was shortened, and certain parts of the curriculum were removed. Duwe and Clark (2015) found that program integrity matters for recidivism outcomes, for the results showed that high-fidelity Moving On reduced reoffending whereas low-fidelity Moving On did not.

3. Participation in the low-fidelity Moving On, SOAR, PRI, and MCORP programs was mandatory, whereas involvement in educational programming (including secondary and postsecondary degrees), chemical dependency treatment, and sex offender treatment was more coercive. Participation in the remaining 14 interventions/program effects was completely voluntary.

4. A copy of the data set that has been stripped of any identifying information may be obtained from the primary author upon request.

5. The specialization/diversity items measure the extent to which offenders specialized in felonies, violent crimes, drug offenses, and so on. The formula for calculating the specialization/diversity measures is adapted from research that has examined offending specialization/diversity for offenders in general (Agresti & Agresti, 1978; Mazerolle, Brame, Paternoster, Piquero, & Dean, 2000; Sullivan, McGloin, Pratt, & Piquero, 2006). To illustrate, the following is the formula we used to measure violent offending specialization/diversity: 1 – ((Violent Offense Convictions/Total Convictions) * (Violent Offense Convictions/Total Convictions)). A value of “0” for this item indicates the offender has complete specialization in violent offenses, whereas a value of “1” indicates complete diversity of offending.

6. EMPLOY is not an acronym but is the actual name of the program, which focuses on delivering employment assistance and services to offenders during the last 3 months of their confinement and up to 12 months following their release from prison.

7. A few points of clarification are in order regarding the warehousing rate of 31%. First, the warehousing rate reported here measures the absence of participation in any intervention. In contrast, the idle rate reported by the MnDOC measures offenders who are capable of working but have not been assigned, have been terminated from their assignments, or have refused an assigned placement. Second, the MnDOC’s idle rate, which has recently ranged between 16% to 18%, is quite a bit lower than the warehousing rate of 31%. However, the idle rate is a one-day snapshot of the prison population, whereas the warehousing rate reported here looks at all offenders released between 2003 and 2011. As we show later on, warehoused offenders are more likely to have shorter lengths of stay in prison, which results in a higher warehousing rate for a cohort of released prisoners than it would be for a one-day snapshot of the prison population.

8. The 60% of offenders who participated in any URRI includes those who participated in SRRIs as well as those who did not.

9. We assessed the robustness of the reconviction findings by estimating Cox and logistic regression models on the 16 comparisons using rearrest as the recidivism measure. Among the 32 models we estimated, the results were slightly different in only two of the models. Although the effect for SRRIs was statistically significant in the four intervention logit model for reconviction, it was not significant for rearrest (p = .08). On the other hand, though the effect for SRRIs was not statistically significant in the five or more intervention logit model for reconviction, it was statistically significant for rearrest. Other than these two differences, however, the results for rearrest and reconviction were virtually indistinguishable from each other.

10. As the data in Table 6 suggest, offenders who participated in only one intervention or two or more interventions were more likely to be involved in voluntary programming.

11. In addition to providing what is arguably an overly optimistic perspective on the viability of significantly changing system-wide recidivism rates, the Pew Center on the States (2011) report contains inaccurate recidivism data, at least for Minnesota. For example, the report indicates 61% of Minnesota prisoners released in 2004 returned to prison within 3 years. Using our data set, which includes all offenders released from Minnesota prisons in 2004, we see that 52% returned to prison within 3 years. The Pew report states that 36% of Minnesota prisoners released in 2004 returned to prison within 3 years for a new crime and that another 26% returned for a technical violation. The MnDOC data show, however, that 25% returned to prison for a new felony and 38% returned for a technical violation. Because 11% came back to prison more than once during the 3-year follow-up period for a new felony and a technical violation, the overall return to prison rate was 52%. It is unclear whether the errors in the Pew report apply only to Minnesota or whether the rate data for other states are inaccurate, too.

12. Along with limited funding and brief stays in prison, the availability of physical space within correctional facilities would likely be another constraint to providing effective interventions to all offenders. Although the physical space needs tend to vary by the type of program, most programs need space for classrooms (for the delivery of program services) and offices (for staff). The lack of available programming space may be due, in part, to correctional facilities that were designed and constructed, often decades ago, to meet the needs of punishment and security rather than rehabilitation. But part of it may also be due to facilities that are operating at, or above, their bed space capacities.

13. In addition to temporal differences, any comparison made between our findings and the estimates reported earlier (J. Austin, 2001; Lynch & Sabol, 2001) is confounded by variations in how programming is being defined and the type of prison population being studied. Rather than focusing on prison labor and vocational and educational programming, we used a relatively broad definition of institutional programming. Moreover, in contrast to prior estimates, which have been based on one-day snapshot populations, we looked at a sample of released prisoners. Given the findings presented here, we anticipate the warehousing rate would be higher for a sample of released prisoners compared to a snapshot of the prison population due to the increased “churn” observed for shorter-stay offenders such as probation and release violators.

14. As noted earlier, 62% of the 55,656 releases from prison in this study had been admitted to prison most recently as a probation or parole violator. This rate is consistent not only with older data on the percentage of probation and parole violators among all prison admissions for states like Ohio, Oregon, and California (Parent, Wentworth, Burke, & Ney, 1994), but also with more recent data from states such as Utah (Office of the Utah Legislative Auditor General, 2013) and Missouri (Missouri Working Group on Sentencing and Corrections, 2011).

15. One might be tempted to conclude that because longer confinement periods are associated with greater involvement in programming, which is, in turn, linked with reduced recidivism, we are recommending an across-the-board increase in lengths of imprisonment. On the contrary, if U.S. sentencing and correctional policies were rooted more in rehabilitation than in just deserts, we suspect that imprisonment periods would be longer for the short-stay offenders and shorter for those with lengthy sentences. For example, let us assume we have an offender with a 10-year imprisonment period. Given that it would likely take, at most, several years for this offender to participate in multiple effective interventions in prison, the balance of this prisoner’s confinement time would only be serving the goals of punishment and perhaps incapacitation. Therefore, we anticipate that even relatively modest decreases in the confinement periods of prisoners with longer sentences would not unduly limit participation in programming and, thus, would likely have a negligible impact on public safety. Just as important, trimming the confinement periods for prisoners with longer sentences would help reduce the size of the prison population and, by extension, correctional costs.