Journal of Quantitative Criminology

, Volume 13, Issue 1, pp 73–92 | Cite as

The effectiveness of service work: An analysis of recidivism

  • Ronit Nirel
  • Simha F. Landau
  • Leslie Sebba
  • Bilha Sagiv


The Israeli “service work” law of 1987 enables a court to commute prison sentences of up to 6 months to service work in the community. This paper examines the correctional effectiveness of this new sanction by comparing the rate of recidivism (over a period of 14 months) among 407 offenders sentenced to service work to that of 950 comparable offenders sentenced to imprisonment. As the research design is quasi-experimental, an adjustment for confounders is carried out using the propensity score (PS) methodology. The estimation of the odds ratio of recidivism with respect to sanction comprises two steps: (a) the PS, which is the conditional probability of assignment to a particular sanction given a set of confounders, is estimated by a logistic model; and (b) the conditional probability of recidivism, given the PS and other covariates, is estimated by a second model. The findings indicate that before an adjustment for the systematic differences between the two sanctions was carried out, the odds for recidivism among prisoners were 2.4 times higher than the odds for service workers. After the adjustment, the odds ratio was reduced to 1.7. This estimate indicates that the service work sanction has a considerable correctional effect. The need to address additional criteria for the effectiveness of service work (e.g., net-widening) is emphasized.

Key words

correctional effectiveness community sanction Israel propensity score observational study 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Central Bureau of Statistics (1968).Criminal Statistics 1964, 1965, Jerusalem.Google Scholar
  2. Cochran, W. G. (1968). The effectiveness of adjustment by subclassification in removing bias in observational studies.Biometrics 24: 295–313.Google Scholar
  3. Cox, D. R., and Snell, E. J. (1989).Analysis of Binary Data, Chapman and Hall, London.Google Scholar
  4. Drake, C. (1993). Effects of the propensity score on estimators of treatment effect.Biometrics 49: 1231–1236.Google Scholar
  5. Drake, C., and McQuarrie, A. (1995). A note on bias due to omitted confounders.Biometrika 82: 633–638.Google Scholar
  6. Eden, R. (1990).The Effects of Probation as Compared with Imprisonment on the Prevention of Recidivism, M.A. thesis, University of Haifa, Haifa, Israel.Google Scholar
  7. Hosmer, D. W., and Lemeshow, S. (1989).Applied Logistic Regression, Wiley, New York.Google Scholar
  8. Israel Prison Service (1991).Annual Report 1991, Jerusalem.Google Scholar
  9. Landau, S. F., Sebba, L., Sagiv, B., Nirel, R., and Peles, Y. (1994).Punishment by “Service Work”—An Evaluation Study, Technical report, The Hebrew University of Jerusalem, Jerusalem, Israel.Google Scholar
  10. Maltz, M. D. (1984).Recidivism, Academic Press, New York.Google Scholar
  11. Martinson, R. (1974). What works? Questions and answers about prison reform.Public Interest 35: 22–54.Google Scholar
  12. McCarthy, B. R. (ed.) (1987).Intermediate Punishments: Intensive Supervision, Home Confinement and Electronic Surveillance, Criminal Justice Press, Monsey, NY.Google Scholar
  13. Morris, N., and Tonry, M. (1990).Between Prison and Probation, Oxford University Press, Oxford.Google Scholar
  14. Palmer, T. (1992).The Re-emergence of Correctional Intervention, Sage, Newbury Park, CA.Google Scholar
  15. Pugatsch, N., and Tousson, Z. (1981). Penal labor as an alternative to short prison terms.Crime Soc. Deviance 9: 102–110.Google Scholar
  16. Rosenbaum, P. R., and Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects.Biometrika 70: 41–55.Google Scholar
  17. Rosenbaum, P. R., and Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score.J. Am. Stat. Assoc. 79: 516–524.Google Scholar
  18. Rubin, D. B. (1973). Matching to remove bias in observational studies.Biometrics 29: 159–183.Google Scholar
  19. Santer, T. J., and Duffy, D. E. (1989).The Statistical Analysis of Discrete Data, Springer-Verlag, New York.Google Scholar
  20. Sebba, L. (1969). Penal reform and court practice: The case of the suspended sentence. In Drapkin, I. (ed.),Scripta Hierosolymitana, Vol. XXI. Studies in Criminology, Magnes Press, Jerusalem, pp. 138–170.Google Scholar
  21. Sebba, L. (1979). Amnesty—a quasi-experiment.Br. J. Criminol. 19: 5–30.Google Scholar
  22. Shoham, S., and Sandberg, M. (1963). Suspended sentences in Israel: An evaluation of the preventive efficacy of prospective imprisonment.Crime Delinq. 10: 74–85.Google Scholar

Copyright information

© Plenum Publishing Corporation 1997

Authors and Affiliations

  • Ronit Nirel
    • 1
  • Simha F. Landau
    • 2
  • Leslie Sebba
    • 2
  • Bilha Sagiv
    • 2
  1. 1.Department of StatisticsThe Hebrew University of Jerusalem, Mt. ScopusJerusalemIsrael
  2. 2.Institute of Criminology, Faculty of LawThe Hebrew University of Jerusalem, Mt. ScopusJerusalemIsrael

Personalised recommendations