The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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<strong>The</strong> Present Study <strong>The</strong> overall aim <strong>of</strong> the present study is to undertake a comprehensive review and synthesis <strong>of</strong> the most rigorous research available on the effects <strong>of</strong> probation supervision intensity on recidivism. <strong>The</strong> focus <strong>of</strong> the review is programs that include among their primary features a change in the ratio <strong>of</strong> probationers to probation <strong>of</strong>ficers (caseload size), frequency <strong>of</strong> contact between <strong>of</strong>ficers and clients, or other ‘frontline’ supervisory behavior, such as drug testing. <strong>The</strong> effects <strong>of</strong> these changes are tested against a counterfactual <strong>of</strong> ‘supervision as usual’ – <strong>of</strong>fenders who remained part <strong>of</strong> standard probation caseloads. <strong>The</strong> primary outcome measure is recidivism, as measured by arrests, charges, or convictions. We also examine the impact <strong>of</strong> probation intensity on technical violations. As we have seen, there is conflicting evidence about the effectiveness <strong>of</strong> increasing the intensity <strong>of</strong> probation supervision. It may depend on the specific philosophies and components <strong>of</strong> the programs and how they interact with supervision levels. <strong>The</strong> risk and need levels, and other characteristics, <strong>of</strong> <strong>of</strong>fenders who participated in ISP research studies may also impact the relative effectiveness <strong>of</strong> the programs. We systematically code the characteristics <strong>of</strong> each program and sample to examine which, if any, <strong>of</strong> these characteristics moderate the overall effect <strong>of</strong> the change in intensity. <strong>The</strong> specific research questions we address in this systematic review are: 1. How does the degree <strong>of</strong> probation supervision intensity affect probationers’ subsequent <strong>of</strong>fending and technical violations? 2. To what extent does program philosophy (treatment, surveillance, or hybrid) influence the success or failure <strong>of</strong> changes in supervision intensity? 9
3. To what extent do the risk/need levels <strong>of</strong> program participants affect their response (in terms <strong>of</strong> re<strong>of</strong>fending and violations) to changes in supervision intensity? 4. Which other program components or <strong>of</strong>fender characteristics moderate the overall effect <strong>of</strong> supervision intensity on crime? Systematic Review Methodology Criteria for inclusion and exclusion <strong>of</strong> studies in the review Types <strong>of</strong> Interventions Eligible studies will test the effect <strong>of</strong> a change in intensity <strong>of</strong> probation supervision on subsequent crime. A change in intensity could be brought about by increasing or decreasing the ratio <strong>of</strong> clients to probation <strong>of</strong>ficers (changing caseload size); increasing or decreasing the frequency <strong>of</strong> contact between clients and their <strong>of</strong>ficers; or increasing or decreasing the frequency <strong>of</strong> other forms <strong>of</strong> supervisory control effected by probation <strong>of</strong>ficers, such as drug testing. 4 Studies in which the primary purpose <strong>of</strong> the research design is to estimate the impact <strong>of</strong> these specific measures on recidivism and/or technical violations are considered. Most studies have tested increases in intensity rather than decreases, but changes in both directions are eligible for inclusion in the review. We impose a number <strong>of</strong> restrictions on program type in order to preserve comparability between what we already know will be a highly diverse set <strong>of</strong> studies. Some programs have examined the provision <strong>of</strong> supervision as part <strong>of</strong> a ‘team’ approach; for example, multi-agency collaboration between probation <strong>of</strong>ficers, police <strong>of</strong>ficers, and 10
Page 1 and 2: University of Penn
Page 3 and 4: In memory of Edwar
Page 5 and 6: Janel McCaffrey and Knakiya Hagans,
Page 7 and 8: traditional practice, we find no ev
Page 9 and 10: Methodology .......................
Page 11 and 12: LIST OF FIGURES Figure 1.1: Effect
Page 13 and 14: intensity makes no difference to re
Page 15 and 16: isk of committing
Page 17 and 18: impact of probatio
Page 19 and 20: which perhaps suggests that ISP is
Page 21 and 22: program intended to reduce the stra
Page 23: supervision with probation
Page 27 and 28: Methods Scale (SMS: Farrington et a
Page 29 and 30: Types of Outcomes
Page 31 and 32: Description of met
Page 33 and 34: actual behavior. We analyze technic
Page 35 and 36: Treatment of quali
Page 37 and 38: treatment group, and those to the r
Page 39 and 40: Discussion of Resu
Page 41 and 42: were evaluated in the same report (
Page 43 and 44: direction of effec
Page 45 and 46: To what extent does program philoso
Page 47 and 48: Which other components of</
Page 49 and 50: .450; technical violations: Q B < .
Page 51 and 52: it should be noted that those progr
Page 53 and 54: up in unpublished reports than thos
Page 55 and 56: violations first went before a judg
Page 57 and 58: 2 One U.S. estimate indicates that
Page 59 and 60: Tables Table 1.1: Characteristics <
Page 61 and 62: Table 1.3: Moderator Variable <stro
Page 63 and 64: Table 1.4: Moderator Variable <stro
Page 65 and 66: Figures Figure 1.1: Effect
Page 67 and 68: Figure 1.5: Effect of</stro
Page 69 and 70: CHAPTER 2. ‘Low-Intensity
Page 71 and 72: What Works in Probation Supervision
Page 73 and 74: to do with it. Furthermore, the mor
Page 75 and 76:
to the New York City and Oregon stu
Page 77 and 78:
Barnes et al. (forthcoming) have su
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paradox.” He suggests that ‘not
Page 81 and 82:
fatal shootings in Philadelphia are
Page 83 and 84:
the proportions of
Page 85 and 86:
Interventions and Follow-Up Probati
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officers more <str
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1. Does the effect of</stro
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all, resulting in a large number <s
Page 93 and 94:
Differential treatment take-up and
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control group members who received
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effect of LIS on r
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incarcerated must also be removed f
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offenders in our s
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ecidivists in the sample, 77 commit
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(IRR = 1.41, p ≤ .107). SES did n
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probability of fai
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The count model ou
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estimate is also practically identi
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twice the risk of
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an end. On the other hand, research
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low-intensity supervision would imp
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Conclusion The aim
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We found that low-risk of</
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7 LIS participants who were transfe
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Tables Table 2.1: Sample Characteri
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Table 2.3: Frequency of</st
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Table 2.5: Instrumental Variables M
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Table 2.7: Prevalence of</s
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Table 2.9: Time to Failure (Violent
Page 135 and 136:
Table 2.12: Treatment Effect by Sub
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Table 2.14: Frequency of</s
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Table 2.16: Instrumental Variables
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Figures Figure 2.1: Risk-Based Allo
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Figure 2.5: Survival Time for LIS E
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CHAPTER 3. Risk Prediction for Effe
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sensitivity of the
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Programs should be designed to adhe
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weight information in an appropriat
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statistical model that would predic
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The Philadelphia m
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assignment pool. Backfill probation
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Little research has been done on th
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already predicted to be at low risk
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It assumes that if of</stro
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involved. Crimes that obviously met
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We examine the potential interactio
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age is based on this date regardles
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obberies. The only
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of low-intensity s
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classified as low risk. The
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All the risk ratios in Table 3.9 in
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0.55. Raising the threshold results
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are partly selected on the basis <s
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make up the majority of</st
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strategy allows probation o
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Notes 1 In this study, murder, atte
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Table 3.2: Sample Characteristics (
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Table 3.6: Predictive Ability at Al
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Table 3.9: Post-Random Assignment O
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APPENDICES Appendix A: Systematic R
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combination. The s
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B. ELIGIBILITY CHECKLIST B1. First
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Other: txcxloth C6d. Additional pro
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D. SAMPLE LEVEL CODING SHEET Instru
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E. DEPENDENT VARIABLE CODING SHEET
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F14. Comparison group sample size f
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weight w is then recalculated (6),
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Study Sheffield (Males) 1976 (Folka
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Study Dallas TX 1992 (Turner & Pete
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Study Minnesota ISR 1995 (Deschenes
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Study Clark WA 2003 (Barnoski, 2003
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Study Whatcom WA 2003 (Barnoski, 20
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Study Los Angeles CA 2005 (Zhang &
Page 223 and 224:
Fed. Prob., 56, 12-17. Turner, Pete
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Study Reference Benekos & Sonnenber
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Study Reference Giblin (2002) Using
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Study Reference Lasater et al. (n.d
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Study Reference Robertson (2000) Co
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Study Reference Turner & Greene (19
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Appendix E: Philadelphia APPD Low-<
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Prevalence of Reci
Page 239 and 240:
Frequency of Recid
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Instrumental Variables Model: Preva
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Instrumental Variables Model: Preva
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Post-RA Months in Jail and Probabil
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Scaled Schoenfeld Residuals Time =
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BIBLIOGRAPHY Chapter 1 ** Denotes t
Page 251 and 252:
Cook, T. D., & Campbell, D. T. (197
Page 253 and 254:
Glaze, L. E, & Bonczar, T. P. (2009
Page 255 and 256:
MacKenzie, D. L. (2006a). What work
Page 257 and 258:
Petersilia, J., Turner, S., & Desch
Page 259 and 260:
safety first: 13 strategies for suc
Page 261 and 262:
Wilson, D. B. (2010). Meta-analysis
Page 263 and 264:
Angrist, J. D. (2006). Instrumental
Page 265 and 266:
Clear, T. R., & Hardyman, P. L. (19
Page 267 and 268:
period266.pdf Lowenkamp, C. T., Lat
Page 269 and 270:
Rosch, J. (2006). Deviant peer cont
Page 271 and 272:
Taxman, F. S., & Thanner, M. (2006)
Page 273 and 274:
statistical learning. Journal <stro
Page 275 and 276:
Federal Bureau of
Page 277 and 278:
Marsh, K., & Fox, C., (2008). <stro
Page 279:
Sherman, L. W. (1993). Defiance, de
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