Introduction

At the end of 2021, over 800,000 persons were on parole following incarceration in the United States,[1] and over 16,000 were on parole in Illinois.[2] Yet within three years, nearly 40% of the people released from Illinois prisons returned, at an estimated cost of over $150,000 each return.[3] Those released to the community from prison face many obstacles in finding employment, which is a key component to successful reentry and is an important factor in reducing recidivism.[4] Finding employment after prison can reduce economic motives for crime, can act as an informal control, and can help to facilitate achievement of goals.[5] As nearly all individuals who are in prison are eventually released back to the community, programs that support reintegration back into society are important for reducing recidivism and saving taxpayer dollars.

Generally, work release centers allow individuals nearing the end of their sentences an opportunity to work in the community while still in prison, returning during non-working hours to the correctional facility.[6] These programs expanded greatly in the United States in the 1970s.[7] They are designed to provide prisoners with opportunities to gain work experience and save money prior to release.[8] They also potentially strengthen ties between the participants, their families, and their communities, thereby aiding participants in reintegration.[9]

Illinois Work Release Centers

The Illinois Department of Corrections (IDOC) operates four work release centers called Adult Transition Centers (ATCs). A current contractual vendor for two sites is the Safer Foundation (Table 1). Individuals who meet eligibility requirements can apply or be transferred to ATCs if they are nearing the end of their prison sentence with less than 30 months left.[10] These programs are designed to enable individuals obtain employment while serving the remainder of their prison sentence and to reintroduce them to aspects of independent living within the community.

ATC participants work or engage in this programming daily and return to the ATCs overnight. Participants are placed in program levels that start at level one and end at level four. ATC staff assesses progress and movement to higher levels every 30 days. Each level requires at least 35 hours of employment per week; education, public services, or vocational education; compliance with established individual program goals; and an absence of disciplinary issues. As participants progress through the level system and move closer to their release date, they are allotted more privileges. Earned privileges include more time to leave the facility for personal time and can include overnight stays with family (e.g., spend time with family, dining out).

Table 1

Illinois Adult Transition Centers by Population

Table1

a Population as of January 13, 2019.

Note. IDOC = Illinois Department of Corrections. Information from IDOC website at https://www2.illinois.gov/idoc/facilities/Pages/adulttransitioncenters.aspx

Prior Research

Prior research has found that work release programs can help increase employment and moderately reduce recidivism outcomes after release.[11] For example, a 2014 study of Illinois Adult Transition Centers (ATCs) found participation modestly increased employment outcomes.[12] A Minnesota evaluation found work release participants recidivated at lower levels than a comparison group but increased the risk for revocation for technical violations.[13] In addition, participation in work release half-way houses in New Jersey has reduced parole revocation and, in turn, the rate at which individuals return to prison.[14]

Current Study

The current study examined the impact Illinois ATCs have on different participants based on their characteristics, which can help in tailoring programming to improve outcomes.[15] Prior studies have found participant characteristics such as age, arrest history, offense type, and risk levels can predict success or failure in the work release program.[16] One study found high-risk offenders were less likely to be rearrested or reconvicted than a comparison group.[17]

In the current study, we used state administrative prison and arrest records to answer the following research questions:

  • What were the characteristics of ATC participants?
  • How did characteristics of participants vary by ATC facility?
  • What were the differences in recidivism outcomes (rearrest and reincarceration) by ATC facility?
  • What were the differences in recidivism outcomes by ATC participant characteristics?

Methods

We used state administrative prison and arrest records to answer the research questions. The project was approved under full review from the ICJIA Institutional Review Board.

Sample

The sample comprised 1,580 ATC participants who exited in 2016 and 2017. Most were males, about half were Black and half White, with an average age of 38 at release (Table 2). Participants averaged 10.9 prior arrests in Illinois each, and just over half of the sample had no prior Illinois prison stays (n = 821). Over one-third of all ATC participants were at the Crossroads ATC. A total of 11.9% of the sample had prior ATC stays (n = 188). Of them, 89.4% had one prior ATC stay (n = 168); 10.1% had two prior stays (n = 19); and one person had three prior ATC stays. The average ATC stay was less than one year (10.8 months). See Table 2 for Class offenses in the ATC sample.

For comparison, 53,047 persons exited IDOC in 2016 and 2017. Of them, 97% were male, 58.2% were Black, and their mean age was 35.5 (SD = 11.9). In addition, 8.6% had Class X offenses, 29% had Class 1, 30% had Class 2, 16.5% had Class 3, and 34.8% had Class 4.

Table 2

Demographics of Sample

Table2

Note. Sample size was 1,580. Percentages may not equal 100% due to rounding. SD = Standard deviation.

Data Sources

State Arrest Data

ICJIA Center for Criminal Justice Data and Analytics (CCJDA) staff pulled arrest data from the Illinois State Police Criminal History Record Information (CHRI) system. The CHRI system contains information required by statute to be submitted on each arrested person by arresting agencies, state’s attorney’s offices, circuit courts, and state and county correctional institutions for the purpose of creating a cumulative history of events.[18] ICJIA has access to most information in the CHRI System through ISP’s off-line, ad hoc database for research purposes.

State Corrections Data

We used prison exit files provided to ICJIA by IDOC for data analysis and research purposes. Upon initial admission to an IDOC facility each incarcerated individual is assigned a unique IDOC number, which is kept for subsequent IDOC incarcerations. The files provide such information as demographics, offense convictions, and dates of entry and exit. CCJDA staff also retrieved data from Offender 360 on movement of prisoners to and from IDOC facilities. Offender 360 is an online case management system used by IDOC to catalog and store additional prisoner information. In sum, CHRI provided prior arrests and post-ATC arrests from 1968 to the end of 2021, and Offender 360 provided facility movement data.

Procedure

CCJDA staff pulled a sample of 1,731 ATC participants released in 2016 and 2017 from IDOC exit files. The files included prior prison exits and post-ATC exits from 1989 to the end of 2020. We removed the following from the sample: nine individuals with multiple ATC participations during the time period, 17 who stayed less than one month in an ATC, and four persons who died in custody. Using IDOC records, CCJDA staff matched the resulting sample of 1,701 with first name, last name, and date of birth on the records, supplemented with automated and manual checks. The outcome was a 92.9% match for a final sample size of 1,580.

Analytic Strategy

We analyzed the data using IBM SPSS 24 (Statistical Package for the Social Sciences) to run descriptive statistics, chi-square tests, and linear regressions, in which the outcomes were rearrest and reincarceration post-ATC participation. The follow up time from ATC release to rearrest was up to 6 years, and for reincarceration it was up to 5 years depending on release date.

Recidivism Risk Proxy Score

During the time period examined, IDOC did not reliably use a recidivism risk tool to provide a risk score.[19] Risk assessment tools typically include variables in our statistical models such as age and criminal history. Lacking these tools at the time, we used a risk proxy score in place of them. We created the score based on a method to create a risk proxy score as established by and validated by Wong and colleagues[20] and replicated in other studies.[21] Those in the sample were scored based on age at first arrest, the number of prior arrests, and current age. Age at first arrest was scored as younger than 21 = 3, 21-23 = 2, and 24 or older = 1. Number of prior arrests (before ATC participation) was scored as seven or more arrests = 3, 3-6 arrests =2, and 0-2 arrests = 1. Current age (age at ATC exit) was scored as 33 or younger= 2, 34-37 = 1, and 38 or older = 0. The Wong et al. proxy score values provide higher scores for people who are younger, who have more prior arrests, and who are younger at first arrest. This pattern follows the risk need responsivity (RNR) model, which assists in assigning program placement for correctional populations.[22]

Regression Analyses

For linear regression, dependent variables were rearrest and reincarceration following ATC participation. The independent variables included gender; race; age at ATC exit; prior arrests; prior prison exits; prior ATC participation; holding offense class; holding offense type; ATC facility type (contractual or State-operated); ATC facility name; and ATC length of stay (as specified in Table 2). We dichotomized variables of participant characteristics as follows: gender (1= male, 0 = female); race (1 = White, 0 = Other race); age at IDOC exit (1 = 18-30 years old, 0 = 31 or older); prior arrests (1 = 0-10, 0 = 11 or more); prior prison stays (1 = 1 or fewer, 0 = 1 or more); prior ATC participation (1= one or more treatments, 0 = no prior ATC treatment); ATC facility type (1 = state operated, 0 = contractually operated); ATC facility [Crossroads (1 = yes, 0 = no)]; ATC facility [Peoria (1 = yes, 0 = no); ATC length of stay (1= less than 1 year, 0 = 1 year or more); low recidivism risk [1 = moderate/high risk (score of 5+) and 0 = low risk (score of 1-4)].

We also analyzed holding offense class and type of offense for which a conviction led to imprisonment and subsequent ATC participation. We coded offenses as 1 = more serious felony classes (classes X, 1, and 2) and 0 = less serious felony classes (classes 3 or 4). In Illinois, aside from Class M/murder, Class X is the most serious felony. It has the longest sentencing range of 6 - 30 years in prison. Class 4 is the lowest felony offense class, with a sentence range of 1 – 3 years in prison.[23] Only persons convicted of felony offenses rather than misdemeanors can be sentenced to IDOC facilities. In addition, we examined offense type as violent; property; drug; motor vehicle or driving under the influence (DUI); and “other.” “Other” included escape, forgery, deception or fraud, government or business bribery, and other sex offenses. We dichotomized offense types as 1 = violent, 0 = non-violent; 1 = property, 0 = non-property; 1 = drug, 0 = non-drug; 1 = motor vehicle or DUI. We did not dichotomize “other.”

Study Limitations

One limitation is that we were unable to reliably obtain several characteristics from IDOC records that could potentially affect recidivism following ATC participation. These data include current or prior employment status or employment characteristics, such as income level, education, disciplinary records, housing status, mental health, existence of substance use or substance abuse disorder, and physical health. Another limitation is that we had to use a recidivism risk proxy score based on available variables to estimate risk rather than rely on a recidivism risk tool. In addition, we examined participants released in 2016 and 2017 to ensure adequate follow up time, but the policies and practices of the time may not reflect the current operations.

Findings

A total of 48% of the ATC sample had zero Illinois rearrests (n = 759) and 86.5% had zero Illinois reincarcerations (n = 1,366). Of the 52% of participants with at least one post-release arrest (n = 821), the average number of rearrests was three (SD = 2.7), ranging from one to 20 across this group. Of the 14% reincarcerated (n = 214), the average number of reincarcerations was 1.2 (SD = 0.5), ranging from one to four.

Participant Characteristics by ATC Facility

We examined ATC participants by facility (Table 3). In the two non-Chicago ATC facilities, a majority of participants were White, while, in the Chicago facilities, a majority of participants were Black. The women participants at Fox Valley were slightly older than men in the other facilities when they exited the ATC. They also had lower recidivism risk scores. North Lawndale participants had slightly higher mean prior arrests, mean prison stays, and mean ATC participation than the participants in other facilities.

Table 3

Participant Characteristics by ATC Facility

Table3

Note. Sample size was 1,580 except where otherwise noted. Percentages may not equal 100% due to rounding. Offense class and type were the highest offense conviction that led to prison and to ATC participation.

We ran chi-square tests to examine the relationship between participant characteristics and ATC facility. Many participant characteristics differed based on the ATC facility in which the person participated. For instance, we found a significant relationship between a participant having a motor vehicle/DUI offense conviction (thereby leading to a prison stay and ATC participation) and the ATC facility in which they participated, X2 (3, N = 1572) = 27.905, p < .01. We also found significant relationships between property offenses and ATC facility, X2 (3, N = 1572) = 14.051, p < .01; and between violent offenses and ATC facility, X2 (3, N = 1572) = 11.928, p < .01. In addition, we found significant relationships between prior ATC treatments and ATC facility, X2 (3, N = 1572) = 16.131, p < .01; between prior prison exits and ATC facility, X2 (3, N = 1572) = 28.152, p < .01; between classes of offense and ATC facility, X2 (3, N = 1572) = 8.163, p < .05; and between recidivism risk scores and ATC facility, X2 (3, N = 1572) = 59.320, p < .01.

Differences in ATC Participants and Rearrest

Linear regression was performed to examine ATC participant demographics and rearrest, R2 = .126, F(1, 14) = 17.243, p < .001 (Table 4). Males were more likely than females to be rearrested after ATC participation. We found a higher likelihood of rearrest among ATC participants younger than 30 with moderate to high recidivism risk scores, more than 10 prior arrests, and more than 1 prior prison stay than with participants over 30 with lower recidivism risks. Moreover, participants convicted of a violent offense were more likely to be rearrested than participants with non-violent convictions.

ATC participants in state-operated facilities rather than in state contracted facilities were less likely to be arrested after release. However, there were other confounding factors, such as whether contractual facilities were located in the city of Chicago and whether participants had higher proportions of prior arrests and prior prison stays as well as moderate/high recidivism risk scores. Those who participated in ATCs for less than a year were more likely to be rearrested than those with longer participation. We found no statistically significant differences in rearrest after ATC participation when examining race, offense type, offense class, or ATC facility.

Table 4

Linear Regression of ATC Participant Characteristics and Rearrest

Table4

Note. Sample size was 1,580 except for prior arrest and recidivism risk was 1,572. Data from Illinois Department of Corrections and Illinois State Police’s Criminal History Record Information database. CI = confidence interval; LL = lower limit; UL = upper limit. *p < .05. **p < .01.

Differences in ATC Participants and Reincarceration

We ran linear regression to examine participant characteristics and reincarceration, R2 = .063, F(1, 14) = 7.476, p < .001 (Table 5). Males and younger participants were more likely to be reincarcerated following ATC participation than females and older participants. Participants who were less likely be incarcerated after ATC participation had been in prison for a property offense rather than non-property offense, had a drug offense rather than non-drug offense, and had a motor vehicle/DUI rather than non-motor vehicle/DUI. Findings show no statistically significant difference in reincarceration for those with a violent offense compared to those with a non-violent offense. Finally, those who participated in a state operated ATC facility were less likely to be reincarcerated than those who stayed in a contractual ATC facility, but again, the facility location and respective participants were notably different.

Table 5

Regression of ATC Participant Characteristics and Reincarceration

Table5

Note. Sample size was 1,580. CI = confidence interval; LL = lower limit; UL = upper limit. *p < .05. **p < .01.

Discussion

We examined Illinois prison and arrest records to learn about participants of work release centers and to examine factors associated with recidivism outcomes. We found age, gender, and ATC facility were associated with rearrest and reincarcerations. In addition, we found recidivism risk, offense type, prior arrests and incarcerations, and length of stay were associated with rearrest. Based on our findings we offer suggestions for programmatic enhancement, but we acknowledge that some suggestions may require additional resources.

Consistently Measure and Use Recidivism Risk, Needs, and Responsivity

Of all ATC participants during the time period examined, a large majority—more than three-fourths—were in the moderate to high recidivism risk score category. As expected, those in the moderate to high recidivism risk category were more likely to be rearrested than those with low risk. The risk principle suggests interventions are most effective when more intensive programming is matched to individuals with moderate to high risk.[24] In addition, dynamic risk factors, sometimes called criminogenic needs, can be measured and considered in corrections.[25] By definition, these factors can be changed to reduce recidivism, The risk need responsivity (RNR) framework is well-established and implemented and can assist in assigning program placement and services for correctional populations.[26] Routh and Hamiliton (2015) found support for the RNR framework in work release programming.[27] During the time period of this study, IDOC did not use a recidivism risk tool, but has since employed one, the Ohio Risk Assessment System (ORAS).[28] Going forward, the ATCs should administer and use the ORAS findings in order to tailor programming and additional supports for ATC participants.

Provide Additional Supports to Younger Participants

We found younger participants were more likely to be rearrested and reincarcerated following ATC participation than older participants. This finding is supported by prior research on work release programs.[29] Re-entry for young adults is difficult because they are still developing the skills to make good decisions while transitioning from prison to the community.[30] Emerging adults who exit prison often lack trustworthy confidants and struggle in coping with the burden of responsibilities of independence and emerging adulthood.[31] The Council of State Governments’ recommended services facilitate getting family involved and getting connected to supportive services as ways to help young adults navigate the transition back to the community and into adulthood.[32] A study by Mizel et al. (2020) found young people felt building strong and valued relationships with program staff boosted their confidence in their ability to stay out of prison.[33] In the same study, young people expressed a desire for programs that met their basic needs and for programs that started while they were still inside and continued after release to aid in the transition. Finally, programs have proven to be more successful when they are tailored to and focus on the individuals’ wants and needs.[34]

Offer Additional Programmatic Support to Violent Offenders

We found participants convicted of a violent offense were more likely to be rearrested than those with nonviolent offenses. This finding has been supported by other research on prisoners.[35] It has been suggested that improving protective factors[36] and using victim-offender mediation techniques could be useful to help those who have committed violent crimes to develop empathy and understand the impact of their actions in a prison setting.[37] More research should be done on innovative programs to identify and offer services to violent offenders who do not respond to existing services.[38]

Consider Length of ATC Participation

In our study, those who participated in ATCs for less than a year were more likely to be rearrested than those with longer participation. In prior research, a longer dosage of correctional programming was associated with reduced recidivism.[39] However, the length of program dosage should be tied to recidivism risk (i.e., those with higher risk should have a higher dosage).[40] However, with this linkage, more research should be done on to examine optimal dosage and the impact of length of participation in ACT programs on recidivism.

Standardize ATCs Based on Best Practices

There were differences in recidivism outcomes by ATC facility type (state operated or state contracted). However, participant characteristics were different based on the ATC facilities in which they participated, including offense type and class, recidivism risk score, number of prior ATC participation, and number of prior prison exits. More research is needed to uncover the best practices at the ATC facilities that yield better outcomes. This study is part of a larger one that includes qualitative interviews with ATC staff and employers of participants that can further add to what appears to be working. Further research on work release centers is warranted, using comparison groups and particularly randomized control trials when possible.[41]

Conclusion

We examined 1,580 work release participants in IDOC ATCs who exited prison in 2016 and 2017, and we tracked their post-release arrests and incarcerations through 2021. Most participants in the sample were male, about half were Black and half were White, and their average age at release was 38. The average stay at an ATC was 10.8 months. Several participant characteristics differed based on the ATC facility in which a person participated, including prior ATC treatment, prior prison exits, offense type, class of offense, recidivism risk score, and recidivism.

We ran linear regressions on ATC participant characteristics and post-release rearrest and reincarceration. We found the following ATC participants more likely to be rearrested and re-incarcerated: males, those younger than age 30 at time of release, and those who participated in contractually operated facilities. In addition, we found the following ATC participants were more likely to be rearrested: those with moderate to high recidivism risk, those with a violent offense conviction, those with more than 10 prior arrests, those with one or more prior incarcerations, and those with less than one year ATC participation. A prior study of work release programming found similar results with participant characteristics, including age, arrest history, offense type, and risk levels predicting recidivism.[42]

We suggest some potential ways to enhance the work release programs. These suggestions include assessing recidivism risk and needs and supporting younger and violent offenders in particular. In addition, we recommend having participants stay in the program for at least one year for better outcomes. Finally, since some facilities have better outcomes, we recommend uncovering and standardizing best practices across facilities.

The authors would like to thank Dr. Karl Gruschow, Manager of the Center for Criminal Justice Data and Analytics at ICJIA for his assistance on the project, as well as Dr. Timothy Lavery. The authors would like to thank IDOC current and former staff for their assistance including James Pagano, Sharon Shipinski, and Alyssa Williams, as well as Safer Foundation staff including Harry Alston, Victor Dickson, Benjamin Osbourne, Sodiqa Williams, and Mark Yates.

  1. Kaeble, D. (2023). Probation and parole in the United States, 2021. U.S. Department of Justice, Office of Justice Programs. Bureau of Justice Statistics. https://bjs.ojp.gov/sites/g/files/xyckuh236/files/media/document/ppus21.pdf ↩︎

  2. Illinois Department of Corrections. (n.d.). Prison exit data sets. https://idoc.illinois.gov/reportsandstatistics/prison-exit-data-sets.html ↩︎

  3. Moreno, V., Firfer, N., Harris, K., Beck, A., Rudolph, A., Wolff, P., & McDonald, F. (n.d.). Re-entry housing issues in Illinois: The current situation, challenges, and possible solutions. Metropolitan Planning Council and Illinois Justice Project. https://www.metroplanning.org/uploads/cms/documents/re-entry_housing_issues_report_final.pdf ↩︎

  4. Nally, J. M., Lockwood, S., Ho, T., & Knutson, K. (2014). Post-release recidivism and employment among different types of released offenders: A 5-year follow-up study in the United States. International Journal of Criminal Justice Sciences, 9(1), 16.; Western, B., & Sirois, C. (2019). Racialized re-entry: Labor market inequality after incarceration. Social Forces, 97(4), 1517-1542. https://doi.org/10.1093/sf/soy096; Kolbeck, S. G., Bellair, P. E., & Lopez, S. (2022). Race, work history, and the employment recidivism relationship. Criminology, 60(4), 637-666. https://doi.org/10.1111/1745-9125.12317; LaBriola, J. (2020). Post-prison employment quality and future criminal justice contact. RSF: The Russell Sage Foundation Journal of the Social Sciences, 6(1), 154-172. https://doi.org/10.7758/RSF.2020.6.1.07 ↩︎

  5. LaBriola, J. (2020). Post-prison employment quality and future criminal justice contact. RSF: The Russell Sage Foundation Journal of the Social Sciences, 6(1), 154-172. https://doi.org/10.7758/RSF.2020.6.1.07 ↩︎

  6. Duwe, G. (2015). An outcome evaluation of a prison work release program: Estimating its effects on recidivism, employment, and cost avoidance. Criminal Justice Policy Review, 26(6), 531-554. https://doi.org/10.1177/0887403414524590 ↩︎

  7. Turner, S., & Petersilia, J. (1996). Work release in Washington: Effects on recidivism and corrections costs. The Prison Journal, 76(2), 138-164. ↩︎

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  9. Jung, H. (2014). Do prison work-release programs improve subsequent labor market outcomes? Evidence from the adult transition centers in Illinois. Journal of Offender Rehabilitation, 53(5), 384-402. https://doi.org/10.1080/10509674.2014.922158 ↩︎

  10. 20 Illinois Admin. Code § 455 (2022). ↩︎

  11. Duwe, G. (2013). What works with Minnesota prisoners: A summary of the effects of correctional programming on recidivism, employment and cost avoidance. Minnesota Department of Corrections.; Visher, C. A., Kachnowski, V., La Vigne, N. G., & Travis, J. (2004). Baltimore prisoners’ experiences returning home. The Urban Institute. ↩︎

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  13. Duwe, G. (2015). An outcome evaluation of a prison work release program: Estimating its effects on recidivism, employment, and cost avoidance. Criminal Justice Policy Review, 26(6), 531-554. https://doi.org/10.1177/0887403414524590 ↩︎

  14. Routh, D., & Hamilton, Z. (2015). Work release as a transition: Positioning success via the halfway house. Journal of Offender Rehabilitation, 54(4), 239-255. https://doi.org/10.1080/10509674.2015.1024909 ↩︎

  15. Routh, D., & Hamilton, Z. (2015). Work release as a transition: Positioning success via the halfway house. Journal of Offender Rehabilitation, 54(4), 239-255. https://doi.org/10.1080/10509674.2015.1024909 ↩︎

  16. Routh, D., & Hamilton, Z. (2015). Work release as a transition: Positioning success via the halfway house. Journal of Offender Rehabilitation, 54(4), 239-255. https://doi.org/10.1080/10509674.2015.1024909 ↩︎

  17. Zweig, J., Yahner, J., & Redcross, C. (2011). For whom does a transitional jobs program work? Examining the recidivism effects of the Center for Employment Opportunities program on former prisoners at high, medium, and low risk of reoffending. Criminology & Public Policy, 10(4), 945-972. https://doi.org/10.1111/j.1745-9133.2011.00766.x ↩︎

  18. 20 ILCS 2635/1 see https://www.ilga.gov/legislation/ilcs/ilcs3.asp?ActID=351&ChapterID=5 ↩︎

  19. In 2020, the ORAS was selected and used for all persons entering IDOC at intake. (A. Williams, personal communication, July 17, 2023). ↩︎

  20. Wong, T. (2009). Validation of the state of Hawaii LSI-R proxy. http://icis.hawaii.gov/wp-content/uploads/2013/07/copy2_of_copy_of_SARA-DVSIExploratory-Study-Oct-2008.pdf ↩︎

  21. Bogue, B., Woodward, W., & Joplin, L. (2006). Using a proxy dcore to pre-screen offenders for risk to reoffend. Center for the Study and Prevention of Violence.; Lowder, E. M., Foudray, C. M. A., & McPherson, M. (2022). Proxy assessments and early pretrial release: Effects on criminal case and recidivism outcomes. Psychology, Public Policy, and Law, 28(3), 374–386. https://doi.org/10.1037/law0000341; Reichert, J., Powers, M., & Skorek, R. (2016). Housing and services after prison: Evaluation of the St. Leonard’s House reentry program. Illinois Criminal Justice Information Authority. ↩︎

  22. Andrews, D. A., & Bonta, J. (2010). Rehabilitating criminal justice policy and practice. Psychology, Public Policy, and Law, 16(1), 39. https://doi.org/10.1037/a0018362; Polaschek, D. L. L. (2012). An appraisal of the Risk–Need–Responsivity (RNR) model of offender rehabilitation and its application in correctional treatment. Legal and Criminological Psychology, 17(1), 1–17. https://doi.org/10.1111/j.2044-8333.2011.02038.x; Wormith, J. S., & Zidenberg, A. M. (2018). The historical roots, current status, and future applications of the Risk-Need-Responsivity Model (RNR). In E. L. Jeglic & C. Calkins (Eds.), New frontiers in offender treatment: The translation of evidence-based practices to correctional settings (pp. 11–41). Springer International Publishing. https://doi.org/10.1007/978-3-030-01030-0_2 ↩︎

  23. 730 ILCS 5/5-4.5-25 through 730 ILCS 5/5-4.5- 45 ↩︎

  24. Andrews, D., Bonta, J., & Hoge R. (1990). Classification for effective rehabilitation: Rediscovering psychology. Criminal Justice and Behavior 17,19-52.; Andrews, D. A., Zinger, I., Hoge, R., Bonta, J., Gendreau, P. and Cullen F. T. (1990). Does correctional treatment work? A clinically relevant and psychologically informed meta-analysis. Criminology, 28, 369-404.; Lowenkamp, C. T., Latessa, E. J., & Holsinger, A. (2006). The risk principle in action: What we have learned from 13,676 offenders and 97 correctional programs. Crime and Delinquency, 52 (1).; Lowenkamp, C. T. Latessa E. J., & Smith, P. (2006). Does correctional program quality really matter? The impact of adhering to the principles of effective intervention. Criminology and Public Policy, 5, 575-594.; Van Voorhis, P. (2007). An overview of offender classification systems. In P. Van Voorhis, D. Lester, & M. Braswell (Eds.) Correctional counseling and rehabilitation. Anderson Publishing. ↩︎

  25. Ward, T., & Fortune, C. A. (2016). The role of dynamic risk factors in the explanation of offending. Aggression and Violent Behavior, 29, 79-88. https://doi.org/10.1016/j.avb.2016.06.007 ↩︎

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