The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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supervision model, or ‘supervision as usual’ (SAU). Under SAU, <strong>of</strong>fenders were supervised in regional units based on their residence, unless they were ordered by the court or APPD to be supervised in a specialist unit (e.g., sex <strong>of</strong>fender or mental health units). Offenders in APPD’s active caseload who were previously assigned to the West or Northeast regional units and were predicted to be low risk according to the prediction model described above were randomly assigned to LIS or SAU. In total, 1,559 <strong>of</strong>fenders were randomly assigned: 800 to the LIS (treatment) group (400 from each region), and 759 to the control group (401 in the West and 358 in the Northeast). 3 Probation clients assigned to the treatment group were placed in a caseload <strong>of</strong> four hundred. Two probation <strong>of</strong>ficers handled the entire low-intensity caseload. Probationers received only one <strong>of</strong>fice visit every six months, with telephone reporting appointments every six months and approximately halfway between <strong>of</strong>fice visits (see Appendix E for full details <strong>of</strong> the LIS model). <strong>The</strong>y were returned to standard supervision if they were arrested for a new crime, because the LIS probation <strong>of</strong>ficers’ caseloads were too large to handle the extra work required to process these cases. <strong>The</strong> experiment followed an ‘intention-to-treat’ analysis (Montori & Guyatt, 2001), so those <strong>of</strong>fenders who were randomly assigned but could not be supervised in the low-intensity caseload due to failure or other operational issues were analyzed in their assigned groups rather than according to the type <strong>of</strong> supervision they actually received. In order to maintain the integrity <strong>of</strong> the LIS model, LIS <strong>of</strong>ficers’ caseloads were kept at 400 by topping them up with so-called ‘backfill’ cases: <strong>of</strong>fenders from the existing APPD caseload who were also predicted to be low-risk but were not part <strong>of</strong> the random 141
assignment pool. Backfill probationers were not included in the analysis <strong>of</strong> the main results <strong>of</strong> the experiment. SAU for the control group usually consisted <strong>of</strong> monthly <strong>of</strong>fice visits, although the frequency could be increased or decreased at the probation <strong>of</strong>ficer’s discretion for reasons relating to compliance or time left on the probation term. <strong>The</strong>y continued regular appointments with their usual probation <strong>of</strong>ficer and no part <strong>of</strong> their supervision changed as a result <strong>of</strong> their experimental status. Probationers and probation <strong>of</strong>ficers were not informed <strong>of</strong> their status. Caseloads in this group were still large enough (approximately 145 clients per <strong>of</strong>ficer) that the content <strong>of</strong> meetings was essentially the same in both the treatment and control groups. However, control group <strong>of</strong>fenders saw their probation <strong>of</strong>ficers more frequently. Treatment group cases received approximately 45 per cent fewer contacts than they had in the year prior to random assignment, while the amount <strong>of</strong> contact in the control group did not change. Control group <strong>of</strong>fenders received approximately twice as many contacts as treatment group <strong>of</strong>fenders. <strong>The</strong> experimental protocol called for three control group contacts to every one in the treatment group, or six to one in terms <strong>of</strong> faceto-face contacts (assuming monthly <strong>of</strong>fice-based contacts in the control group), so although this standard was not quite achieved, the treatment group still received lowerintensity supervision. No significant differences in recidivism were found between the treatment and control groups after one year. Sixteen per cent <strong>of</strong> the treatment group and 15 per cent <strong>of</strong> the control group were charged with a new <strong>of</strong>fense <strong>of</strong> any type (p ≤ .593). Thus, it appeared that LIS did not lead to more crime compared to SAU, and was 142
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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
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actual behavior. We analyze technic
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Treatment of quali
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treatment group, and those to the r
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Discussion of Resu
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were evaluated in the same report (
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direction of effec
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To what extent does program philoso
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Which other components of</
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.450; technical violations: Q B < .
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it should be noted that those progr
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up in unpublished reports than thos
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violations first went before a judg
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2 One U.S. estimate indicates that
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Tables Table 1.1: Characteristics <
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Table 1.3: Moderator Variable <stro
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Table 1.4: Moderator Variable <stro
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Figures Figure 1.1: Effect
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Figure 1.5: Effect of</stro
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CHAPTER 2. ‘Low-Intensity
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What Works in Probation Supervision
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to do with it. Furthermore, the mor
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to the New York City and Oregon stu
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Barnes et al. (forthcoming) have su
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paradox.” He suggests that ‘not
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fatal shootings in Philadelphia are
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the proportions of
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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
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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
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
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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
Page 135 and 136: Table 2.12: Treatment Effect by Sub
Page 137 and 138: Table 2.14: Frequency of</s
Page 139 and 140: Table 2.16: Instrumental Variables
Page 141 and 142: Figures Figure 2.1: Risk-Based Allo
Page 143 and 144: Figure 2.5: Survival Time for LIS E
Page 145 and 146: CHAPTER 3. Risk Prediction for Effe
Page 147 and 148: sensitivity of the
Page 149 and 150: Programs should be designed to adhe
Page 151 and 152: weight information in an appropriat
Page 153 and 154: statistical model that would predic
Page 155: The Philadelphia m
Page 159 and 160: Little research has been done on th
Page 161 and 162: already predicted to be at low risk
Page 163 and 164: It assumes that if of</stro
Page 165 and 166: involved. Crimes that obviously met
Page 167 and 168: We examine the potential interactio
Page 169 and 170: age is based on this date regardles
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Page 173 and 174: of low-intensity s
Page 175 and 176: classified as low risk. The
Page 177 and 178: All the risk ratios in Table 3.9 in
Page 179 and 180: 0.55. Raising the threshold results
Page 181 and 182: are partly selected on the basis <s
Page 183 and 184: make up the majority of</st
Page 185 and 186: strategy allows probation o
Page 187 and 188: Notes 1 In this study, murder, atte
Page 189 and 190: Table 3.2: Sample Characteristics (
Page 191 and 192: Table 3.6: Predictive Ability at Al
Page 193 and 194: Table 3.9: Post-Random Assignment O
Page 195 and 196: APPENDICES Appendix A: Systematic R
Page 197 and 198: combination. The s
Page 199 and 200: B. ELIGIBILITY CHECKLIST B1. First
Page 201 and 202: Other: txcxloth C6d. Additional pro
Page 203 and 204: D. SAMPLE LEVEL CODING SHEET Instru
Page 205 and 206: 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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