The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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Continued from previous page Proportion <strong>of</strong> studies with characteristic Quasi-Experiments Total (N=9) (N=47) Experiments (N=38) Sample Characteristics Age <strong>of</strong> sample b Juveniles 42.1 44.4 42.6 Youth and adults 52.6 55.6 53.2 Gender c All males 29.0 44.4 31.9 All females 5.3 0.0 4.3 Mixed 34.2 55.6 38.3 Offender risk level High/mostly high risk 71.1 77.8 72.3 Mixed risk levels/no 29.0 22.2 27.7 assessment Outcome Characteristics Arrest outcomes reported 55.3 77.8 59.6 Technical violation outcomes 42.1 77.8 48.9 reported Conviction outcomes reported 71.1 55.6 68.1 Other outcomes available 39.5 0.0 31.9 Length <strong>of</strong> follow-up period 12 months or less 60.5 88.9 66.0 More than 12 months 39.5 11.1 34.0 Some sections do not add up to 100% due to rounding or missing data. b Data not reported in 2 studies. c Data not reported in 12 studies. Table 1.2: Overall Mean Effect Sizes for Crime Outcomes N Mean 95% C.I. OR Lower Upper Q RCTs Arrests 21 .93 .74 1.17 61.55*** Convictions 27 .98 .85 1.13 20.38 Technical violations 16 1.54 .99 2.39 120.11*** Drug arrests 11 1.18 .86 1.61 11.50 Quasi-experiments Arrests 7 .83 .66 1.04 7.55 Convictions 5 .60 .33 1.11 22.74*** Technical violations 7 1.29 .86 1.94 18.91** ** p ≤ .01; *** p ≤ .001. 45
Table 1.3: Moderator Variable <strong>Effects</strong> (Arrest/Conviction, RCTs) N Q B Mean OR 95% C.I. Lower Upper Study Characteristics Publication type Academic publication 16 1.20 .98 1.48 Government/technical report 13 11.86** 1.01 .78 1.30 Other unpublished 9 .70** .55 .88 Research timeframe 1970s and earlier 6 1.09 .77 1.55 1980s 13 .87 1.00 .76 1.33 1990s and 2000s a 19 .90 .72 1.13 Location <strong>of</strong> study USA 33 .93 .80 1.10 1.10 Non-USA 5 1.17 .79 1.74 Program Characteristics Program type Probation enhancement 36 .99 .84 1.17 1.44 Prison diversion 2 .69 .39 1.23 Reduced caseload component Yes 34 1.01 .87 1.17 3.42 No 4 .65 .41 1.01 Increased contact component Yes 21 1.01 .83 1.22 .49 No 17 .90 .71 1.15 Increased drug testing component Yes 11 .80 .62 1.04 2.76 No 27 1.05 .88 1.24 Prevailing supervision philosophy Control/surveillance 15 .92 .73 1.16 Treatment 6 1.73 1.20 .84 1.72 Hybrid 17 .93 .73 1.17 Target population Probationers 27 .92 .76 1.12 Parolees 5 .65 1.07 .75 1.51 Mixed 6 1.04 .69 1.56 Target <strong>of</strong>fense types Any <strong>of</strong>fending 29 .93 .78 1.10 .92 Specialized caseloads 9 1.10 .81 1.49 Continued Mixed effects (method <strong>of</strong> moments) mean odds ratios * p ≤ .05; ** p ≤ .01. a Categories combined: only one study in 2000s, which had large effect favoring treatment group. 46
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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
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 and 24: supervision with probation
Page 25 and 26: 3. To what extent do the risk/need
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: Tables Table 1.1: Characteristics <
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 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
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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
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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
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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
Page 277 and 278:
Marsh, K., & Fox, C., (2008). <stro
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Sherman, L. W. (1993). Defiance, de
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