The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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<strong>The</strong> <strong>of</strong>fender was potentially in direct violation <strong>of</strong> their probation (had been arrested for a new <strong>of</strong>fense after the start <strong>of</strong> their term <strong>of</strong> supervision). 5 <strong>The</strong> <strong>of</strong>fender had multiple active probation cases, one or more <strong>of</strong> which was not classified as low-risk. Random Assignment Following the exclusions, a final sample <strong>of</strong> 1,559 <strong>of</strong>fenders was put forward for random assignment on October 1, 2007. Note that almost half <strong>of</strong> the probationers with low-risk cases were excluded from the random assignment pool. <strong>The</strong> most common reason for exclusion was having fewer than thirty days remaining on probation (see Fig. 2.2). APPD wanted to test a low-intensity caseload <strong>of</strong> 400 clients per <strong>of</strong>ficer, so the random assignment sequence was designed to allocate 800 <strong>of</strong>fenders to the treatment (LIS) group, with 400 each in the West and Northeast regions. <strong>The</strong> control (SAU) group consisted <strong>of</strong> 759 <strong>of</strong>fenders (401 in the West and 358 in the Northeast). A considerable number <strong>of</strong> the sample were later found to be ineligible for the experiment, some due to potential violations that occurred between the time <strong>of</strong> pre-screening and random assignment, and most others for reasons that arose later that made low-intensity supervision too difficult. 6 A flowchart (Moher et al., 2001) showing exclusions and case flow through each stage <strong>of</strong> the project may be found in Fig. 2.2. <strong>The</strong> experiment followed an ‘intention-to-treat’ analysis (Montori & Guyatt, 2001), so those <strong>of</strong>fenders who were randomly assigned to LIS but subsequently excluded were analyzed in their assigned groups rather than according to the type <strong>of</strong> supervision they actually received. 69
Interventions and Follow-Up Probation clients assigned to the treatment group (LIS) were placed in a caseload <strong>of</strong> four hundred. Two probation <strong>of</strong>ficers handled the entire low-intensity caseload <strong>of</strong> 800 <strong>of</strong>fenders. Clients received a considerably reduced level <strong>of</strong> supervision compared to the standard model described above. <strong>The</strong> full supervision protocol, including details about contact frequency and type, may be found in Appendix E. At their first visit with the low-intensity probation <strong>of</strong>ficer, treatment group subjects were informed that they were in a low-risk caseload and subject to these new reporting requirements. <strong>The</strong>y were told that they would be transferred back to standard supervision if they were arrested for a new crime. Low-intensity <strong>of</strong>ficers were not expected to handle new <strong>of</strong>fenses. However, they were expected to deal with technical violations that did not result in an arrest or warrant (e.g., missed contacts). In order to maintain low-intensity caseload sizes at 400, probationers who were transferred back to standard supervision were replaced by ‘backfill’ cases. <strong>The</strong>se were <strong>of</strong>fenders from the general caseload who had been predicted low-risk but were not initially randomly assigned. <strong>The</strong>se cases are not analyzed as part <strong>of</strong> the experiment, but they ensured the integrity <strong>of</strong> the low-intensity model by keeping caseloads too large for the <strong>of</strong>ficers to spend more time with their low-risk clients. 7 <strong>The</strong> control group received SAU according to the description above. While probation <strong>of</strong>ficers in this group had smaller caseloads and could in theory spend more time working to address <strong>of</strong>fenders’ needs, in practice caseloads were still large enough that the content <strong>of</strong> meetings was essentially the same in both the treatment and control 70
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University of Penn
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In memory of Edwar
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Janel McCaffrey and Knakiya Hagans,
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traditional practice, we find no ev
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Methodology .......................
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LIST OF FIGURES Figure 1.1: Effect
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intensity makes no difference to re
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isk of committing
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impact of probatio
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which perhaps suggests that ISP is
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program intended to reduce the stra
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supervision with probation
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3. To what extent do the risk/need
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Methods Scale (SMS: Farrington et a
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Types of Outcomes
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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
Page 79 and 80: paradox.” He suggests that ‘not
Page 81 and 82: fatal shootings in Philadelphia are
Page 83: the proportions of
Page 87 and 88: officers more <str
Page 89 and 90: 1. Does the effect of</stro
Page 91 and 92: all, resulting in a large number <s
Page 93 and 94: Differential treatment take-up and
Page 95 and 96: control group members who received
Page 97 and 98: effect of LIS on r
Page 99 and 100: incarcerated must also be removed f
Page 101 and 102: offenders in our s
Page 103 and 104: ecidivists in the sample, 77 commit
Page 105 and 106: (IRR = 1.41, p ≤ .107). SES did n
Page 107 and 108: probability of fai
Page 109 and 110: The count model ou
Page 111 and 112: estimate is also practically identi
Page 113 and 114: twice the risk of
Page 115 and 116: an end. On the other hand, research
Page 117 and 118: low-intensity supervision would imp
Page 119 and 120: Conclusion The aim
Page 121 and 122: We found that low-risk of</
Page 123 and 124: 7 LIS participants who were transfe
Page 125 and 126: Tables Table 2.1: Sample Characteri
Page 127 and 128: Table 2.3: Frequency of</st
Page 129 and 130: Table 2.5: Instrumental Variables M
Page 131 and 132: Table 2.7: Prevalence of</s
Page 133 and 134: Table 2.9: Time to Failure (Violent
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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 &
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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
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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
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Cook, T. D., & Campbell, D. T. (197
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Glaze, L. E, & Bonczar, T. P. (2009
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MacKenzie, D. L. (2006a). What work
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Petersilia, J., Turner, S., & Desch
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safety first: 13 strategies for suc
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Wilson, D. B. (2010). Meta-analysis
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Angrist, J. D. (2006). Instrumental
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Clear, T. R., & Hardyman, P. L. (19
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period266.pdf Lowenkamp, C. T., Lat
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Rosch, J. (2006). Deviant peer cont
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Taxman, F. S., & Thanner, M. (2006)
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statistical learning. Journal <stro
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Federal Bureau of
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Marsh, K., & Fox, C., (2008). <stro
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Sherman, L. W. (1993). Defiance, de
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