Predicting Failure on the Sex Offense Registry: An Examination of Static and Dynamic Factors

Abstract

There is considerable research on the efficacy of sex offense registries, but less is known about individual compliance with registration. Recent research and subsequent policy have highlighted the importance of understanding technical violations as a hidden driver of mass incarceration, and there is emerging evidence that suggests that agency violation practices vary widely. We analyzed administrative data from a large sample of individuals on the sex offense registry in Missouri to identify the factors associated with risk for noncompliance, including a technical violation and reincarceration. Both stable and dynamic factors contribute to our understanding of compliance and incarceration. Findings also suggest that living in a county with few registrants contributes to lowered odds of noncompliance. Alternatively, high caseloads contribute to greater odds of incarceration only. More generally, we find a sizeable portion of jurisdictional variation remains for both noncompliance and incarceration, a finding that suggests different enforcement practices across place.

Keywords:

• Sex offense
• SORNA
• failure to register
• recidivism
• risk factor

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In August, 2018 the State of Missouri transitioned to a tier system of registration which allows some terms of supervision and registration to be reduced. The study was completed prior to the change. More information on the registry requirements can be found here - https://www.mshp.dps.mo.gov/MSHPWeb/PatrolDivisions/CRID/SOR/factsheet.html

2 Forty-four persons were listed in the offender file but had no registry entries. 32 of these individuals (73%) came from a single county. This provides early evidence that some variation in the details of RSO status – including registry status – stems from differences in how jurisdictions manage their populations.

3 Prior work suggests that the correlates of recidivism differ substantially between male and females convicted of sexual offenses (Sandler & Freeman, 2009). To appropriately model the interactive effects of sex on predictors and non-compliance and incarceration, multiplicative terms would need to be incorporated into the models, or models should be considered separately. Given the small sample of females in the study, we conducted additional analyses with both males and females and found that an incorporation of a dummy variable in the models to account for baseline risk differences across genders did not substantively change overall findings (See Supplemental Tables 1 & 2), however, small cell-size prevents a more precise modeling how gender interacts with independent and dependent variables. For this reason, our main analyses focus on males only.

4 Unfortunately, with the data provided, we were not able to ascertain the differences between those who simply did not make the registration deadline and were absent from contact for long periods of time. In discussions with local stakeholders, individuals are most likely to be marked as an absconder because they miss regular check in appointments.

5 It is worthy of note that there are few “cross-jurisdiction” moves occurring in our data. Of our sample, we find less than 10 percent of individuals who moved ever left their originating jurisdiction.

Additional information

Funding

This project was supported by Award No. 2013-BJ-CX-K043, awarded by the Bureau of Justice Assistance, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect those of the Department of Justice. The authors are thankful to Ron Beck and Mark Ritchey from the Missouri Statistical Analysis for their help on this project.