The Role of Family Support in the Explanation of Patterns of Desistance Among Individuals Convicted of a Sexual Offense
Bibliographic record
Abstract
Despite the growing body of research on desistance from crime, there have been comparatively few studies that have focused specifically on desistance from sex offending. Much remains unknown about whether the findings from the general desistance literature are applicable to individuals convicted of a sexual offense. The current study explores this issue. Given the well-established importance of the social support network in the process of desistance from crime, this research focuses on the influence of indicators of family support on reoffending outcomes. We also examine the sustained effects of family ties on offending behavior over time. In addition, we look beyond traditional measures of social bonds (i.e., marital status and employment) and assess the impact of the stability of family support on reoffending outcomes. The current research explores the criminal career trajectories of a sample of 318 Canadian individuals convicted of a sexual offense and released back into their communities. Analyses yielded two distinct groups of offenders: one displaying a very low rate of reoffending that continued to decline over the follow-up period, and the other showing a higher rate of reoffending but also with steady declines throughout the observation period. Findings showed that while marriage was not significantly associated with reoffending, stable family support was significantly linked to reduced reoffending. We also found evidence of a sustained effect of family support on reoffending over a 3-year period. These findings underline the importance of expanding beyond the traditional measures of social bonds conventionally used in desistance studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".