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Abstract

Securing stable housing may be difficult for returning offenders in general, and these concerns may be exacerbated for sex offenders. In addition to the barriers faced by other returning offenders, sex offenders face intense stigma and once released to the community, they are also subject to additional legal restrictions. The current study explores the effect of statewide residency restriction policies on housing mobility using a unique sample of male sex offenders released in a Midwestern state. The research is based on a quasi-experimental cohort control group design and it describes the frequency and correlation of movement for pre- and post-statewide residency restriction legislation samples. Sex offenders released after the implementation of residency restrictions moved more often and had relatively high degrees of housing mobility compared to offenders released prior to the legislation. The results have important implications for reentry programming and post-release services for sex offenders.

Notes

This project was funded by the National Institute of Justice, Office of Justice Programs, US Department of Justice (2008-DD-BX-0002). An earlier version of this paper was presented in 2010 at the American Society of Criminology annual meeting in San Francisco. The authors thank William S. Davidson II for his helpful comments. The opinions, conclusions, and recommendations reflect those of the authors and not any aforementioned agency.

1. Schools include any building (public or private) used to educate children under the age of 19. Although some states have local towns that enact stricter boundary zones than the statewide law (Meloy et al., Citation2008), there are no local enhancements in the study state.

2. As an exception, there is a grandfather clause whereby those who were already living or working within the boundary are not required to move. However, if an offender moves, they must comply with the restrictions law.

3. The study state uses a tiered sexual offense classification system based upon contact circumstances. The most serious categories involve sexual penetration or contact with additional conditions of young victim age, coercion, or injury. Less serious categories involve sexual penetration or contact in the absence of aggravating circumstances. Non-contact offenders convicted of gross indecency, child pornography, and computer-based indecency or pornography offenses were excluded from the sample. For our final sample, 46.7% (N = 905) fell into the more serious contact categories, 42.8% (N = 828) fell into the less serious contact categories, and the remaining 10.5% (N = 203) had committed an assault with intent to commit a contact sexual offense.

4. Sex offenders must register and report in-person to a law enforcement agency to verify home address and provide information on education, employment, transportation, and communication activities. Offenders in both groups are not allowed to live in a residence with children under the age of 18 including their own children.

5. The analyses here represent a subsample taken from a larger sample of sex offenders. Geocoding was initially performed on the larger sample, and the subsample was derived after the geocoding process was complete. A minimum match criteria of 60% was used, and those that were not automatically matched were attempted to be matched interactively. Out of 8,374 total addresses, 7,416 (88.6%) were successfully matched at a score of 80-100, 462 (5.5%) were matched with a score lower than 80, 391(4.7%) could not be matched to an address point and had to instead be matched to a zip code centroid, and 105 (1.2%) could not be matched either because they corresponded to an out of state address or no match could be made interactively.

6. To add further clarity regarding the conceptualization of non-residential terms, “commercial placement” refers to initial placements to hotels, motels, and shelters. “Transitional housing” represents initial placements to semi-secure, shared residences that provide transitional services. “Treatment facilities” correspond to initial placements to inpatient centers for treatment of sexual and/or drug use behaviors. “Correctional facilities” refer to secure Department of Corrections’ facilities that are used to provide offenders with treatment services that were required, but not completed while the offender was in an institution or aftercare services.

7. We were able to glean the non-residential parole variable from our data using triangulation. The address data indicated that particular addresses were something other than a residential address, such as hotels, motels, treatment facilities, or correctional facilities. This was determined by review of qualitative agent case notes and subsequent online queries. A limitation is that the parole agent case notes are often incomplete, and in the absence of any indication from case notes or internet queries, we assume the address was a residential location.

8. While it would be ideal to disaggregate the non-white variable into racial/ethnic categories and also consider gender in the present analysis, the sample included very small numbers of Hispanic and female sex offenders.

9. The Department of Corrections utilizes an internal salient factor score risk assessment of assault and property crime risk. The research team only had access to summary risk scores. The majority of risk assessments (70%) were administered at intake, but some were calculated following the offender’s release from prison.

10. We considered restricting the sample to those offenders with 400-800 days on parole in order to make the groups more equitable. Restricting the sample did not change the bivariate relationship between residency restrictions and mobility; therefore, the larger sample was used and conservative estimates provided. An additional concern is that the significant differences in time at risk between the pre-restriction and post-restriction groups. Residential mobility is truncated for those who are returned to prison. Supplementary analyses (not shown) show no significant differences (Χ2(1) = 2.33, p = .311) in recidivism between restriction groups.

11. In our initial analyses, we considered several other models including ordinal logistic, Poisson, and negative binomial regression. The proportional odds assumption test of the ordinal logistic regression model was violated and the Poisson regression suffered from overdispersion. As such, the estimates derived from these models are biased and not used in this study. A two-phase negative binomial regression analysis was used to confirm the results. First, predictors used in the multinomial logistic model were used in the negative binomial model. Second, the time at risk measure in the multinomial logistic model was dropped from the negative binomial model and an alternative measure was used. All of the remaining predictors used in the multinomial logistic model were added to the negative binomial model. The alternative measure transformed the raw count of days at risk into an offset rate variable [log(parole length+.0001)] and was entered as a predictor (Maddala, Citation1983). The findings for this model were consistent with the multinomial logistic regression model.

12. Collinearity diagnostics (variance inflation factors and tolerance) were performed and did not suggest any concerns with model fit.

13. We used an alternative non-residential variable to explore the sensitivity of the finding. The alternative categorical measure contrasted residential placement (0) against commercial (1) and correctional or coerced (2) placement, which includes residence at halfway houses, treatment facilities, or correctional facilities. On average, correctional or coerced placement had the highest rate of movement (M = 2.81, SD= 2.36) and was followed by commercial (M = 2.56, SD= 2.15) and residential (M = 1.69, SD= 1.95). Multivariate modeling with the alternative measure produced similar estimates to the original measure and confirmed the findings of the research.

Additional information

Notes on contributors

Jason Rydberg

Jason Rydberg is a doctoral student at the School of Criminal Justice at Michigan State University. His research interests include criminological and sociological theory and the societal reaction to deviance. His research has recently appeared in Police Quarterly, Journal of Criminal Justice and Security, and European Journal of Criminology.

Eric Grommon

Eric Grommon received his Ph.D. in Criminal Justice from Michigan State University. He is an Assistant Professor in the School of Public and Environmental Affairs at Indiana University-Purdue University Indianapolis. His research interests include research methods, program and policy evaluation, corrections, prisoner reentry, and community crime prevention.

Beth M. Huebner

Beth M. Huebner is an Associate Professor and Director of Graduate Studies in the Department of Criminology and Criminal Justice at the University of Missouri-St. Louis. Her recent research, funded by the National Institute of Justice, considers the efficacy of sex offender residency laws and explores variation in patterns of offending for urban and rural parolees.

Timothy Bynum

Timothy Bynum is a Professor in the School of Criminal Justice at Michigan State University. His research interests include program and policy evaluations of offender reentry programs and various strategies to reduce gang and gun violence. He is the director of the Michigan Justice Statistics Center, which represents the state Criminal Justice Statistical Analysis Center, and the director of the National Archive of Criminal Justice Data at the Inter-university Consortium on Political and Social Research at the University of Michigan.

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