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Reinforcing the impacts of work release on prisoner recidivism: the importance of integrative interventions

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An Erratum to this article was published on 16 May 2017

Abstract

Objectives

We present findings from an evaluation of a large work release program in the Israeli Prison Service. The Israeli program uses an integrative therapeutic approach which combines work release with a series of other program elements. Our main question is whether this integration of multiple program elements leads to strong benefits in terms of reincarceration and re-arrests.

Methods

The study uses a rich administrative database to develop a propensity score matching approach for creating matched treatment (n = 547) and control (n = 547) subjects. The prisoners in the groups are found to be similar on known characteristics after matching. MHbounds methods are used to assess the sensitivity of the results to bias.

Results

Average standardized effect sizes in our study vary between .17 and .31. In general, rehabilitation outcomes observed are much larger than those reported for US evaluations of work release programs.

Conclusions

Work release in Israel is not simply work release, but involves a positive social environment, a high dosage of counseling and therapy, and more general privileges for inmates including furloughs and cultural activities. We argue that our findings suggest the importance of a broader more integrative approach to work release programs to achieve enhanced success in reducing recidivism.

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Notes

  1. We do not include the work release program in Delaware in our review because the focus was specifically on drug offending (see Martin et al. 1999).

  2. Cost benefit outcomes are complex and can provide different conclusions even from evaluations of the same program. For example, two evaluations of Washington’s work release program evaluated the effects of these programs on correctional costs (Drake 2007; Turner and Petersilia 1996). The latter found that, in general, the program did not reduce costs, mostly due to a high proportion of drop outs (about a third). In contrast, Drake (2007) noted that the Washington work release program brought a cost avoidance benefit of nearly $1700 per participant.

  3. The majority of immigrants to Israel are received under this law, though there is also citizenship through naturalization and family reunification. We only have data on immigrants who came to Israel under the law of return.

  4. An alternative approach commonly used is to simply predict recidivism controlling for the impacts of potential confounding factors. In this approach, if a variable is excluded and it is related to the variable of interest (in this case the treatment), the estimate of the variable of interest would be biased. In the PSM approach, the researcher is not directly estimating the variable of interest, but rather calculating the propensity score. Accordingly, even if variables are excluded, where they are strongly correlated with variables in the PSM model, the bias in the propensity score will be reduced.

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Authors and Affiliations

  1. Institute of Criminology, Faculty of Law, Hebrew University, Jerusalem, Israel

    David Weisburd, Badi Hasisi, Gali Aviv & Noam Haviv

  2. Department of Criminology, Law and Society, Center for Evidence-Based Criminology, George Mason University, Fairfax, USA

    David Weisburd

  3. Ashkelon Academic College, Ashkelon, Israel

    Efrat Shoham

Authors
  1. David Weisburd
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  2. Badi Hasisi
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  3. Efrat Shoham
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  4. Gali Aviv
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  5. Noam Haviv
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Corresponding author

Correspondence to Badi Hasisi.

Additional information

In the original version of this article, some errors were retained in copy-editing. These errors have been corrected herein.

An erratum to this article is available at http://dx.doi.org/10.1007/s11292-017-9291-5.

Appendices

Appendices

Appendix A: list of variables for psm analysis

  • Socio-demographic data

    • Age of entry into program/age at potential entry into program (for comparison group)

    • New Immigrant (yes/no)

    • Marital status (married/not married)

    • Number of children

    • Nationality (Jewish/non-Jewish)

    • Reported years of education

  • Criminal background

    • Incarceration history (number of incarcerations)

    • Calculated age at first incarceration

  • Current Offense

    • Offenses:

      • Violent offense (yes/no)

      • Drug offense (yes/no)

      • Property offense (yes/no)

      • Sexual offense (yes/no)

    • Calculated length of imprisonment (release date minus date of imprisonment)

    • Year of release

  • Prisoner profile (yes/no)

    • Criminal violence

    • Domestic violence

    • Chronically ill

  • Prison experience - data on prisoner during incarceration (until entry into rehabilitation/last potential date for entering rehabilitation)

    • Employment:

      • Number of standardized workdays in contract work

      • Number of standardized workdays in factories (productive factories)

    • Education:

      • Standardized number of formal courses before program entry

      • Standardized number of informal courses before program entry

    • Disciplinary hearings:

      • Standardized number of hearings before program entry

      • Standardized number of hearings that resulted in isolation, before program entry

      • Time between date of last hearing and entry into program

    • Professional training courses:

      • Standardized number of professional training courses before program entry

      • Standardized number of non-professional training courses before program entry

    • Privileges:

      • Standardized number of privileges revoked before program entry

      • Time between date of last revocation and program entry

    • Furloughs:

      • Standardized number of furloughs before program entry

Appendix B: encoding the release committees

At first, before encoding the relevant variable “treatment”, we went over some 100 release committee files from beginning to end to check for mentions of previous treatment given to the prisoner. This included marking relevant words that indicated the existence of the variable “treatment” at any point throughout the incarceration. Given the number of release committees, an algorithm was written to enable quick and easy detection of the variable. The algorithm uses predetermined relevant words and checks them against all the committee files.

The relevant words included in the algorithm: “MAGASH” (Hebrew acronym for “rehabilitation center”), project, division.

The file contained 5404 committees relating to 3523 prisoners (some prisoners appeared before two or more committees). These prisoners include all participants in the group rehabilitation project and all potential prisoners for the comparison group. Of these, 185 participated in a rehabilitation center program, 260 took part in the project, and 431 were on a therapy ward. In total, 780 prisoners were treated. To rule out algorithm search errors, all committees in which one of the relevant words was detected were examined. For instance, if the word “division” appeared but in fact referred to something else, such as the welfare division, the encoding was changed and the committee was removed from the file.

The final stage consisted of checking this variable in the two groups created by propensity score matching: 547 rehabilitation prisoners and 547 comparison group prisoners.

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Weisburd, D., Hasisi, B., Shoham, E. et al. Reinforcing the impacts of work release on prisoner recidivism: the importance of integrative interventions. J Exp Criminol 13, 241–264 (2017). https://doi.org/10.1007/s11292-017-9285-3

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