The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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Study Contra Costa Co CA 1990 (Petersilia & Turner, 1990) Los Angeles Co CA 1990 (Petersilia & Turner, 1990) Ventura Co CA 1990 (Petersilia & Turner, 1990) Atlanta GA 1992 (Petersilia, Turner, & Deschenes, 1992b) Research Design Randomized controlled trial Randomized controlled trial Randomized controlled trial Randomized controlled trial Population Adults convicted <strong>of</strong> felony and misdemeanor drug use, drug dealing, and nonviolent drugrelated crime. Adults convicted <strong>of</strong> felonies and classified as high risk. Adults convicted <strong>of</strong> felonies and classified as high risk or convicted <strong>of</strong> serious crime. Prisoners released to ISP or probationers due to be revoked and returned to prison. Drug involved, high risk/need. Intervention 40:1 caseload, 1 face-to-face contact/drug test and 2 phone calls per week, gradually reduced. Employment assistance, counseling, and links with law enforcement. 33:1 caseload, 3-5 face-to-face contacts and 2 phone calls per week, gradually reducing. Monitoring checks. 19:1 caseload, 4 face-to-face contacts, 2 phone calls, 1 drug test per week, plus monitoring checks, gradually reduced. Employment assistance, victim awareness, links with law enforcement. Augmented ISP with increased surveillance (passive monitoring, <strong>of</strong>ficer checks). 40:3 caseload. Rehabilitation, employment, drug tests, monitoring <strong>of</strong> activities. Same contact level as controls. Comparison 150-200:1 caseload, infrequent, discretionary contact, random drug tests, employment assistance. 250:1 caseload, 1 face-to-face contact per month. Existing ISP. 50:1 caseload, 2 face-to-face visits and 1 phone call per month, no victim awareness. Existing ISP. 12 face-to-face, 10 phone per month, random drug tests, job verification weekly. Outcome Treatment group more likely to fail on technical violations and arrests. No difference for convictions. Treatment group more likely to fail on technical violations, arrests, and convictions. Treatment group less likely to fail on technical violations, arrests, and convictions. Treatment group more likely to fail on technical violations, arrests, and convictions. No convictions in control group. 197
Study Dallas TX 1992 (Turner & Petersilia, 1992) Des Moines IA 1992 (Petersilia, Turner, & Deschenes, 1992b) Houston TX 1992 (Turner & Petersilia, 1992) Santa Fe NM 1992 (Petersilia, Turner, & Deschenes, 1992b) Research Design Randomized controlled trial Randomized controlled trial Randomized controlled trial Randomized controlled trial Population Adult property <strong>of</strong>fenders (mostly male), initially in prison and high risk <strong>of</strong> recidivism on parole. Probationers and parolees convicted <strong>of</strong> drug <strong>of</strong>fense or burglary with drug abuse history. Adult property <strong>of</strong>fenders (mostly male), initially in prison and high risk <strong>of</strong> recidivism on parole. Probationers and parolees with high risk and need. Intervention 25:1 caseload with 10 contacts per month – mix <strong>of</strong> in-person <strong>of</strong>fice/home visits & telephone. Employment assistance, discretionary drug testing. 35:1 caseload. Initially 16 faceto-face, 4 phone contacts and 8 drug tests per month, gradually decreasing. Curfew. Emphasis on urinalysis, unannounced visits and collateral contact Treatment and employment mandated. 25:1 caseload with 10 contacts per month – mix <strong>of</strong> in-person <strong>of</strong>fice/home visits & telephone. Employment assistance, discretionary drug testing. 35:2 caseload. Initially 12 faceto-face contacts, 8 unannounced home visits, 4 drug tests per month. <strong>The</strong>rapeutic approach: counseling, job development, group therapy. Comparison 85:1 caseload, 1 <strong>of</strong>fice visit per month, occasional home visits, no drug testing requirement. 70:1 mixed caseload, routine supervision, risk determines contact levels. Most on highest level: 2 face-to-face and 2 collateral/month. Discretionary testing. 85:1 caseload, 1 <strong>of</strong>fice visit per month, occasional home visits, no drug testing requirement. 60:1 caseload, routine supervision, 2 face-to-face and 1 <strong>of</strong>fice visit per month, discretionary testing and treatment referral. Outcome Treatment group more likely to fail on technical violations, arrests, and convictions. Treatment group more likely to fail on technical violations, less likely on arrests and convictions. Treatment group more likely to fail on technical violations and arrests, but less likely on convictions. Treatment group less likely to fail on technical violations, more likely on arrests and convictions. 198
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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
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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
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
Page 171 and 172: obberies. The only
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
Page 207 and 208: F14. Comparison group sample size f
Page 209 and 210: weight w is then recalculated (6),
Page 211: Study Sheffield (Males) 1976 (Folka
Page 215 and 216: Study Minnesota ISR 1995 (Deschenes
Page 217 and 218: Study Clark WA 2003 (Barnoski, 2003
Page 219 and 220: Study Whatcom WA 2003 (Barnoski, 20
Page 221 and 222: Study Los Angeles CA 2005 (Zhang &
Page 223 and 224: Fed. Prob., 56, 12-17. Turner, Pete
Page 225 and 226: Study Reference Benekos & Sonnenber
Page 227 and 228: Study Reference Giblin (2002) Using
Page 229 and 230: Study Reference Lasater et al. (n.d
Page 231 and 232: Study Reference Robertson (2000) Co
Page 233 and 234: Study Reference Turner & Greene (19
Page 235 and 236: Appendix E: Philadelphia APPD Low-<
Page 237 and 238: Prevalence of Reci
Page 239 and 240: Frequency of Recid
Page 241 and 242: Instrumental Variables Model: Preva
Page 243 and 244: Instrumental Variables Model: Preva
Page 245 and 246: Post-RA Months in Jail and Probabil
Page 247 and 248: Scaled Schoenfeld Residuals Time =
Page 249 and 250: 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
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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
Page 275 and 276:
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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