Parole Violations and Revocations in
California: Analysis and Suggestions
for Action
Pretrial Risk Assessment and Case Classification: A Case Study
Restorative Practices in Institutional Settings and at Release: Victim Wrap Around Programs
Pono Kaulike: Reducing Violence with Restorative Justice and Solution-Focused Approaches
Parole Violations and Revocations in California: Analysis and Suggestions for Action
1 This article is based on Grattet, R., Petersilia, J., & Lin, J. (2008). Parole violations and revocations in California, final report for National Institute of Justice, grant number 2005-IJ-CX-0026, Washington, DC: National Institute of Justice. (NCJRS, NCJ 224521). The complete report is available on the NCJRS Web site at http://www.ncjrs.gov/ pdffiles1/nij/grants/224521.pdf and the UCI’s Center for Evidence-Based Corrections Web site at http:// ucicorrections.seweb.uci.edu/pubs.
2 Petersilia, J. (2008). California’s correctional paradox of excess and deprivation. In M. Tonry (Ed.), Crime and justice: A review of research (Crime and Justice, Vol. 37). (pp. 207–278). Chicago, IL: University of Chicago Press.
3 Legislative Analyst’s Office (2008). Judicial & Criminal Justice: 2007–08 Analysis, Sacramento, CA.
4 Fischer, R. (2005). Are California’s recidivism rates really the highest in the Nation? It depends on what measure of recidivism you use. Irvine, CA: UCI Center for Evidence-Based Corrections.
5 Petersilia, J. (2006). Understanding California corrections. Berkeley, California: California Policy Research Center. Report available online at http:// ucicorrections.seweb.uci.edu/pubs.
6 Glaze, L., & Bonczar, T. (2007). Probation and Parole in the United States, 2006. Washington, DC: Bureau of Justice Statistics. (NCJRS, NCJ 220218).
7 U.S. General Accounting Office (1991). Drug treatment: State prisons face challenges in providing services. Report to the Committee on Government Operations, House of Representatives, Washington, DC: U.S. Congress. More estimates can also be found in Bloom, B., Owen, B. & Covington, S. (2003). Gender-responsive strategies— Research, practice and Guiding principles for women offenders. Washington DC: National Institute of Corrections. Report available online at http://archive.gao.gov/t2pbat7/145135.pdf.
8 California Expert Panel on Adult Offender Recidivism Reduction Programming (2007). A roadmap for effective offender programming in California: Report to the California State Legislature. Sacramento, CA: California Department of Corrections and Rehabilitation.
9 Travis, J. (2003). Parole in California, 1980– 2000: Implications for reform. Washington, DC: Urban Institute.
10 Travis, J. (2005). But they all come back: Facing the challenges of prisoner reentry. Washington, DC: Urban Institute.
11 Glaze & Bonczar, Probation and Parole in the United States, 2006 (see note 6).
12 For a listing of these reports, see California Expert Panel on Adult Offender Recidivism Reduction Programming, A roadmap for effective offender programming in California (note 8). Several of these reports were conducted by the Little Hoover Commission and are available at http://www.lhc.ca.gov/ lhcdir/crime.html.
13 Indeterminate sentencing, with a hearing before the parole board, is reserved for California prisoners who have been sentenced to life in prison with the possibility of parole. About 20,000 prisoners (12 percent) in the California prison population have been sentenced to life with the possibility of parole. In 2006, 98.5 of all released California prisoners were placed on post-prison parole supervision.
14 See California Department of Corrections and Rehabilitation (2006). Department Operations Manual, Chapter 8: Adult Parole Operations. Available online at http://www.cdcr.ca.gov/ Regulations/Adult_Operations/docs/DOM/Ch_8_ Printed_Final_DOM.pdf.
15 Petersilia, California’s correctional paradox of excess and deprivation (see note 2).
16 Petersilia, J. and Turner, S. (1993). Intensive probation and parole. In M. Tonry (Ed.), Crime and justice: An annual review of research (Crime and Justice, Vol. 17). (pp. 281–335). Chicago, IL: University of Chicago Press.
17 Welch, S., Combs, M., & Gruhl, J. (1988). Do Black judges make a difference? American Journal of Political Science, 32 (1). 126–136. Sherman, L. (1980). Causes of police behavior: The current state of quantitative research. Journal of Research in Crime and Delinquency, 17. 69–100.
18 Costello, M., Chiricos, T., Burianek, J., Gertz, M., & Maier-Katkin, D. (2002). The social correlates of punitiveness toward criminals: A comparison of the Czech Republic and Florida. Justice System Journal, 23. 191–220. Wilson, G., & Dunham, R. (2001). Race, class, and attitudes toward crime control: The views of the African-American middle class. Criminal Justice and Behavior, 28. 259–278.
19 In 2003 and 2004, the Board returned parolees for 246 homicides, 1,006 robberies, and 691 crimes involving rape or sexual assault—together accounting for 1.5 percent of all criminal violation cases during this time.
20 Helms, R. & Jacobs, D. (2002). The political context of sentencing: An analysis of community and individual determinants. Social Forces, 81: 577–604. Stolzenberg, L., D’Alessio, S., & Eitle, D. (2004). A multilevel test of racial threat theory. Criminology. 42. 673–698.
21 See Martin, B., & Van Dine, S. (2008). Examining the impact of Ohio’s progressive sanction grid, final report for National Institute of Justice, grant number 2005-IJ-CX-0038, Washington, DC: National Institute of Justice. (NCJRS, NCJ 224317).
22 The details of PVDMI and CSRA are available from the California Department of Corrections and Rehabilitation Web site, http://www.cdcr.ca.gov/ News/2008_Press_Releases/Oct_3.html
Pretrial Risk Assessment and Case Classification: A Case Study
1 The author would like to thank Frank Kuzmickus, Director of Lake County Adult Probation Services, whose suggestion to describe Lake County’s risk assessment experience led to this article. Also, the author appreciates the comments from Marie VanNostrand, Ph.D, on earlier drafts of this paper.
2 In 1987 Lake County developed a rudimentary inhouse point scale based on various criteria identified in the literature as being related to pretrial failure. However, its limitations quickly came to light: a bias towards cash bond recommendations and a lack of statistical validation. The instrument became rather meaningless, eventually shelved, and the use of the subjective method continued for several years.
3 PTBS growth actually became the main dynamic behind the ongoing reduction in field contacts, with no fewer than four revisions to the original classification design.
4 In Illinois, there are basically five categories of felony crimes: X, 1, 2, 3, and 4 with “X” being the most serious and “4” being the least serious.
5 In those programs that use an objective risk instrument but also factor in subjective input (a “combination” or hybrid system), nearly fifty percent operate in jurisdictions with over-capacity jail populations. This is lower than the nearly sixty percent over-capacity found in “subjective only” jurisdictions but still higher than the under thirty percent overcapacity found in “objective only” jurisdictions.
6 The 2003 Pretrial Survey data indicate that including an objective component to the bond recommendation decision-making process—such as with the hybrid system—mitigates the apparent jail-crowding impact of subjective-only assessments. It would seem that by introducing objectivity into the process, the deleterious effect of subjectivity is reduced.
7 In the literature of evidence-based practices, this is known as the “risk principle.”
8 The respective calculations for each system are as follows: Level I: 300 x 4 = 1200 field contacts per month; Level II: 50 contacts per month; total field contacts = 1,250. Max: 200 x 2 = 400 field contacts per month; Med: 100 x 1 = 100 field contacts per month; Min: 50 x 1 = 50 residence verifications per month; total field contacts = 550.
9 For example, in 2008 there were 113 more cases terminated from PTBS as a “violation” that customarily would not have been counted as such.
Restorative Practices in Institutional Settings and at Release: Victim Wrap Around Programs
* The paper was supported by funding from the Illinois Long-Term Offender Committee and a previous version of this paper was presented to the Illinois Long-Term Offender Committee in Chicago, Illinois August, 2007.
Pono Kaulike: Reducing Violence with Restorative Justice and Solution-Focused Approaches
1 The authors express their gratitude and thanks to Alan Katz, MD, MPH, Graduate Chair and Epidemiology Professor, Department of Public Health Sciences, University of Hawai‘i, for his kind assistance with this evaluation and his thoughtful review of this paper. Thanks are also tendered to Diane Stowell, LFMT, for her help providing this program; Shona Conley, University of Hawai‘i Spark Matsunaga Institute for Peace student intern, and Anne Hayden, doctoral candidate, Auckland University of Technology, for their assistance with data collection; and to the Hawai’i Friends of Civic & Law Related Education, the Hawai’i Justice Foundation, and the Wallace Alexander Gerbode Foundation, for supporting this work.
2 Effort is made here to avoid labeling people as offenders and victims and uses these terms only for clarity purposes. Deficit-based labels reinforce negative thoughts, behaviors and emotions. While we should disapprove of bad behavior and recognize pain we feel, we should identify strengths, possibilities, and hope. People always have potential and are more than what happens to them and what they have done in the past.
3 These cases were not referred to Pono Kaulike mainly because the sentencing judge did not make the referral.
4 The idea of using restorative justice and having shared meetings with people involved in intimate violence (man against woman), which Pono Kaulike provides, is controversial and has been discussed previously (Walker & Hayashi, 2007).
Estimating the Impact of Kentucky’s Felon Disenfranchisement Policy on 2008 Presidential and Senatorial Elections
1 According to information directly obtained from Kentucky’s Department of Corrections, the average weekly number of non-state/non-federal County prisoners was 9,428 in February 2009. Since daily numbers were unavailable, the stated figure was derived by dividing the weekly average by seven. The total of ex-felons was calculated by dividing Manza and Uggen’s (2006:75-76) ex-felon “very conservative” estimate by voting age population (128,775/3,123,645=0.0412) and then multiplying the resulting figure by the updated voting age population (3,237,501*0.0412). To ensure that the updated disenfranchisement figures were not skewed by procedural changes in felon reenfranchisement, we obtained 1999-January 2009 felon reenfranchisement statewide tallies from Kentucky’s Secretary of State. From 1999-2004, covering the period in which the Manza/Uggen estimate was calculated, the state average reenfranchisement was ((669+572+958+1278+1193+316)/6=) 831 per year. From 2005 to 2008, the rate dropped to just ((253+274+255+1807)/4=) 432. Contemporaneously, African-American male life expectancy is projected to increase from 69.5 years in 2005 to 70.2 years at 2010, which, combined with lower reenfranchisement rates, suggests that the total number of ex-felons would likely increase. As indicated in Table 2, revised estimates suggest only a slight increase in the number of persons under criminal justice supervision; Manza and Uggen’s (2006) felon disenfranchise estimates remain accurate.
2 To avoid overestimation of felon disenfranchisee effects, prisoners and jail inmates were excluded from felon disenfranchisement estimates. Kentucky’s November 2008 turnout was 62.8 percent of registered voters. For purposes of this study, we will assume that felon disenfranchisees would have voted at a similar rate.
The Effect of Participatory Management on Internal Stress, Overall Job Satisfaction, and Turnover Rate among Federal Probation Officers
1 Stressors are defined as “circumstances which place unreasonable or distinctive demands on an individual, and are usually capable of producing emotional/psychological discomfort” (Grossi & Berg, 1991, p. 76).
2 The second set of data from Kansas and Missouri was collected later to have a larger sample and to address the issue of external validity of preliminary findings using the first set of data from Texas.
3 They originally developed twelve items to measure participatory management. However, five items of the original items were excluded, since variables such as job stress, job dissatisfaction and turnover intention may affect an employee’s attitudes, and produce reciprocal effects in the hypothesized model (Myers & Myers, 1995).
4 According to Kaiser’s criterion, in cases of less than 30 original variables, the resulting communalities of factor analysis are recommended to be all greater than .70 (see Stevens, 1992, p. 379).
5 Turnover intention was substantially positively skewed and was transformed by taking the logarithm for further statistical analysis (Tabachnick & Fidell, 1996).
6 A small number of missing values was replaced with the means of the variable. Three extreme outliers were deleted, bringing the sample size to 188. According to variance inflation factor (VIF) scores, no multicollinearity was found.