The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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probation allows deterrence to work because in terms <strong>of</strong> sanctions, the consequences <strong>of</strong> failure are much greater than they are under more intensive conditions. <strong>The</strong> lowerintensity sanction may also result in less stigma for the <strong>of</strong>fender, which may lead to a defiant criminal response. We also suggested that low-intensity probation, by reducing required attendance at the probation <strong>of</strong>fice, may reduce the likelihood that probationers will associate with more serious <strong>of</strong>fenders and strengthen ties with pro-social networks closer to home. Finally, we noted that the idea <strong>of</strong> low-intensity supervision is consistent with strongly-established principles <strong>of</strong> correctional treatment in which only those in the most need <strong>of</strong> services receive them. <strong>The</strong> Philadelphia APPD Low Risk Experiment <strong>The</strong> Philadelphia APPD Low Risk Experiment was designed as a rigorous test <strong>of</strong> a policy <strong>of</strong> reducing the intensity <strong>of</strong> probation supervision for low-risk <strong>of</strong>fenders. <strong>The</strong> Philadelphia experiment is the first to test this proposition using a randomized controlled trial (RCT) design. <strong>The</strong> following section describes the study design and main results. Additional details may be found in Barnes et al. (forthcoming). Background to the experiment Philadelphia’s Adult Probation and Parole Department (APPD), like other probation departments in the U.S., grapples with the problem <strong>of</strong> increased caseloads and limited resources. <strong>The</strong> average caseload <strong>of</strong> a Philadelphia probation <strong>of</strong>ficer is 150 to 200 <strong>of</strong>fenders (Berk et al., 2009). Around 19 per cent <strong>of</strong> people arrested for fatal and non- 65
fatal shootings in Philadelphia are under APPD supervision at the time <strong>of</strong> arrest (Ahlman et al., 2008). Although the amount and intensity <strong>of</strong> supervision does vary across cases and some <strong>of</strong>fenders are mandated (by judges or probation <strong>of</strong>ficers) to specialized units, there is little systematic variation in Philadelphia in the investment <strong>of</strong> resources according to risk. Thus, in most cases, <strong>of</strong>fenders are assumed to be at similar risk <strong>of</strong> serious re<strong>of</strong>fending at baseline, and judgments are modified according to information that becomes available later in the supervision process. 1 Philadelphia’s APPD has around 50,000 clients under supervision at any time. Supervision is usually organized according to the sector <strong>of</strong> the city in which the <strong>of</strong>fender lives, with a smaller number assigned to specialized units for certain types <strong>of</strong> <strong>of</strong>fenders or needs (such as drug-involved or sex <strong>of</strong>fenders). Intake decisions are made by administrative staff based on court orders or the <strong>of</strong>fender’s residence. Within departmental standards and judicial constraints, supervision <strong>of</strong> <strong>of</strong>fenders is highly discretionary. Clients usually see their probation <strong>of</strong>ficer once a month, and receive routine drug tests at some visits, but the <strong>of</strong>ficer can increase or decrease the frequency <strong>of</strong> <strong>of</strong>fice visits as s/he sees fit. Reporting frequency may be increased to weekly or biweekly as a result <strong>of</strong> noncompliance. It may be reduced to as infrequently as once every three months toward the end <strong>of</strong> a successful term, or based on the <strong>of</strong>ficer’s judgment that the <strong>of</strong>fender is not at high risk <strong>of</strong> recidivism. For similar reasons, the <strong>of</strong>ficer may vary the type <strong>of</strong> supervision between <strong>of</strong>fice, telephone, and non-reporting. Starting in 2005, APPD worked with the University <strong>of</strong> Pennsylvania to develop a new approach to supervision. <strong>The</strong>y aimed to allocate the highest risk <strong>of</strong>fenders to more intensive supervision, with a small ratio <strong>of</strong> <strong>of</strong>ficers to clients so that more resources could 66
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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
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
Page 79: paradox.” He suggests that ‘not
Page 83 and 84: the proportions of
Page 85 and 86: Interventions and Follow-Up Probati
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
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Table 2.7: Prevalence of</s
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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
Page 257 and 258:
Petersilia, J., Turner, S., & Desch
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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
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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
Page 271 and 272:
Taxman, F. S., & Thanner, M. (2006)
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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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