The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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LIST OF TABLES Table 1.1: Characteristics <strong>of</strong> Included Studies ...............................................................44 Table 1.2: Overall Mean Effect Sizes for Crime Outcomes............................................45 Table 1.3: Moderator Variable <strong>Effects</strong> (Arrest/Conviction, RCTs).................................46 Table 1.4: Moderator Variable <strong>Effects</strong> (Technical Violations, RCTs) ............................48 Table 1.5: Effect <strong>of</strong> <strong>Intensity</strong> Variation (Arrest/Conviction, RCTs)................................49 Table 1.6: Effect <strong>of</strong> <strong>Intensity</strong> Variation (Technical Violations, RCTs) ...........................49 Table 2.1: Sample Characteristics................................................................................110 Table 2.2: Prevalence <strong>of</strong> Recidivism (All Offenses, 2-Year Follow Up).......................111 Table 2.3: Frequency <strong>of</strong> Recidivism (All Offenses, 2-Year Follow-Up).......................112 Table 2.4: Time to Failure (All Offenses, 2-Year Follow-Up)......................................113 Table 2.5: Instrumental Variables Model: Prevalence <strong>of</strong> Recidivism (All Offenses, 2- Year Follow-Up) .........................................................................................................114 Table 2.6: Treatment <strong>Effects</strong> by Subgroup (All Offenses, 2-Year Follow Up)..............115 Table 2.7: Prevalence <strong>of</strong> Recidivism (Violent Offenses, 2-Year Follow Up)................116 Table 2.8: Frequency <strong>of</strong> Recidivism (Violent Offenses, 2-Year Follow-Up) ................117 Table 2.9: Time to Failure (Violent Offenses, 2-Year Follow-Up) ...............................118 Table 2.10: Time to Failure with Jail-Time Interaction (Violent Offenses, 2-Year Follow- Up)..............................................................................................................................118 Table 2.11: Instrumental Variables Model: Prevalence <strong>of</strong> Recidivism (Violent Offenses, 2-Year Follow-Up)......................................................................................................119 Table 2.12: Treatment Effect by Subgroups (Violent Offenses, 2-Year Follow Up) .....120 Table 2.13: Prevalence <strong>of</strong> Recidivism (Drug Offenses, 2-Year Follow Up)..................121 Table 2.14: Frequency <strong>of</strong> Recidivism (Drug Offenses, 2-Year Follow-Up)..................122 Table 2.15: Time to Failure (Drug Offenses, 2-Year Follow-Up).................................123 Table 2.16: Instrumental Variables Model: Prevalence <strong>of</strong> Recidivism (Drug Offenses, 2- Year Follow-Up) .........................................................................................................124 Table 2.17: Treatment <strong>Effects</strong> by Subgroups (Drug Offenses, 2-Year Follow Up) .......125 Table 3.1: Sample Characteristics (Full Sample)..........................................................173 Table 3.2: Sample Characteristics (Experimental Sample) ...........................................174 Table 3.3: Prevalence and Frequency <strong>of</strong> Post-Risk Assessment Serious Offending by Risk Level...........................................................................................................................174 Table 3.4: Types <strong>of</strong> Post-Risk Assessment Serious Charges by Risk Level..................175 Table 3.5: Predictive Ability at Alternative Thresholds (Model-Defined Severity).......175 Table 3.6: Predictive Ability at Alternative Thresholds (UCR Part I Offenses) ............176 Table 3.7: Predictive Ability at Alternative Thresholds (Victim/Damage Offenses) .....177 Table 3.8: Post-Random Assignment Serious Offending in Experimental Sample........177 Table 3.9: Post-Random Assignment Offending Severity Stratified by Prior History ...178 ix
LIST OF FIGURES Figure 1.1: Effect <strong>of</strong> Intensive Probation on Arrests (RCTs) ..........................................50 Figure 1.2: Effect <strong>of</strong> Intensive Probation on Arrests (Quasi-Experiments) .....................50 Figure 1.3: Effect <strong>of</strong> Intensive Probation on Convictions (RCTs)...................................51 Figure 1.4: Effect <strong>of</strong> Intensive Probation on Convictions (Quasi-Experiments)..............51 Figure 1.5: Effect <strong>of</strong> Intensive Probation on Technical Violations (RCTs).....................52 Figure 1.6: Effect <strong>of</strong> Intensive Probation on Technical Violations (Quasi-Experiments) 52 Figure 1.7: Effect <strong>of</strong> Intensive Probation on Drug Arrests (RCTs) .................................53 Figure 2.1: Risk-Based Allocation Strategies in the Philadelphia APPD ......................126 Figure 2.2: Case Flow Chart for the Philadelphia APPD Low Risk Experiment...........126 Figure 2.3: Survival Time for LIS Experiment Participants, by Assigned Treatment (All Offenses, 2-Year Follow-Up) ......................................................................................127 Figure 2.4: Cox Proportional Hazards Survivor Function by Assigned Treatment (All Offenses, 2-Year Follow-Up) ......................................................................................127 Figure 2.5: Survival Time for LIS Experiment Participants, by Assigned Treatment (Violent Offenses, 2-Year Follow-Up).........................................................................128 Figure 2.6: Cox Proportional Hazards Survivor Function (Violent Offenses, 2-Year Follow-Up)..................................................................................................................128 Figure 2.7: Survival Time for LIS Experiment Participants, by Assigned Treatment (Drug Offenses, 2-Year Follow-Up) ......................................................................................129 Figure 2.8: Cox Proportional Hazards Survivor Function (Drug Offenses, 2-Year Follow- Up)..............................................................................................................................129 Figure 3.1: Philadelphia APPD’s Risk-Based Caseload Stratification ..........................179 x
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: Methodology .......................
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 and 60: 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
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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
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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
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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