The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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Study Reference Hanlon et al. (1999) <strong>The</strong> relative effects <strong>of</strong> three approaches to the parole supervision <strong>of</strong> narcotic addicts and cocaine abusers. Prison J., 79, 163-181. Harrell, Adams, & Gouvis (1994) Evaluation <strong>of</strong> the impact <strong>of</strong> systemwide drug testing in Multnomah County, Oregon Urban Institute Harrell et al. (2003) <strong>The</strong> impact evaluation <strong>of</strong> the Maryland Break the Cycle initiative. Urban Institute. Harris, Gingerich, & Whittaker (2004) <strong>The</strong> ‘effectiveness’ <strong>of</strong> differential supervision. Crime & Delinquency, 50, 235-271. Irish (1990) Crime, criminal justice and probation: preliminary analysis <strong>of</strong> selected programs in the Criminal Division for 1989. Nassau Co. Probation Dept. Jernigan & Kronick (1992) Intensive parole: the more you watch, the more you catch. J. Off. Rehab., 17(3/4), 65-76. Johnson, Austin, & Davies (2003) Banking low-risk <strong>of</strong>fenders: is it a good investment? Inst. on Crime, Justice & Corrections, George Washington Univ. Kurtz & Linnemann (2006) Improving probation through client strengths: evaluating strength based treatments for at risk youth. Western Criminol. Rev., 7, 9-19. Land, McCall & Williams (1990) Something that works in juvenile justice: an evaluation <strong>of</strong> the North Carolina court counselors’ intensive protective supervision randomized experimental project 1987-1989. Evaluation Review 14, 574-606. Reason for Exclusion Primarily a test <strong>of</strong> a treatment program not delivered by probation/parole <strong>of</strong>ficers. Unmatched controls. No <strong>of</strong>fender-level outcomes for posttrial probation experiment. Unmatched controls. Not a test <strong>of</strong> probation supervision intensity (more risk classification). Unmatched controls. Review <strong>of</strong> programs with unmatched comparisons. Unmatched controls. Unmatched controls. Unmatched controls. Some outcomes reported for treatment group only. Supervision provided by juvenile court to mostly non-criminal juvenile status <strong>of</strong>fenders (runaways, truants etc.) 213
Study Reference Lasater et al. (n.d.) School-based probation intervention results with high-risk youth in Montana. Character Development Systems, LLC. Latessa & Travis (1988) <strong>The</strong> effects <strong>of</strong> intensive supervision with alcoholic probationers. J. Off. Counseling, Services & Rehab., 12(2), 175-190. Latessa & Vito (1988) <strong>The</strong> effects <strong>of</strong> intensive supervision on shock probationers. J. Crim. Just., 16, 319-330 Lattimore et al. (2005) Evaluation <strong>of</strong> the juvenile Breaking the Cycle program RTI International/NIJ Martin & Inciardi (1997) Case management outcomes for druginvolved <strong>of</strong>fenders. Prison J., 77, 168-183. Maupin (1993) Risk classification systems and the provision <strong>of</strong> juvenile aftercare. Crime & Delinquency, 39, 90-105. Meisel (2001) Relationships and juvenile <strong>of</strong>fenders: the effects <strong>of</strong> Intensive Aftercare Supervision. Prison J., 81, 206-245. MI Dept <strong>of</strong> Corrections (2002) 530 probationers use automated reporting kiosks (Jan. 17). MI Dept <strong>of</strong> Corrections Staff News Bulletin. MN Office <strong>of</strong> the Legislative Auditor (2005) Community supervision <strong>of</strong> sex <strong>of</strong>fenders: evaluation report. Nath (1974) Intensive Supervision Program: final report. Florida Parole Commission. National Council on Crime & Delinquency (2001) Evaluation <strong>of</strong> the RYSE program: Alameda County Probation Department. 214 Reason for Exclusion Primarily a test <strong>of</strong> cognitivebehavioral therapy. Unmatched controls. Limited matching <strong>of</strong> controls. Higher risk and need <strong>of</strong>fenders selected into treatment group. Not independent <strong>of</strong> larger study in Latessa (1987). Probation component is not a key part <strong>of</strong> the program. Increased supervision and drug testing are outcomes rather than part <strong>of</strong> the process. Primarily a test <strong>of</strong> a treatment program not delivered by probation <strong>of</strong>ficers. No crime outcomes. No comparison group or crime outcomes. Investigates how supervision intensity differs by risk level. No crime outcomes. No evaluation data reported. No indication that an evaluation was conducted. No evaluation data or crime outcomes reported. Insufficient data to calculate effect sizes: sample sizes not provided for recidivism outcomes. Pre-trial program examining placement into treatment and services.
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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
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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
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 and 212: Study Sheffield (Males) 1976 (Folka
Page 213 and 214: Study Dallas TX 1992 (Turner & Pete
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: Study Reference Giblin (2002) Using
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
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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