Understanding how sexual offenders compare across psychiatric and correctional settings: examination of Canadian mentally ill sexual offenders
Bibliographic record
Abstract
Much of what is known about sexual offenders is based on correctional samples and then applied across settings based on the assumption that this group is homogeneous. In this study, 149 files were compared, including 108 cases from the forensic mental health system (FMH) and 41 cases from the correctional system (COR). Although many similarities were observed between the FMH and COR groups, the results also revealed important differences. The FMH group was characterised by more frequent hospitalisations, higher rates of major mental illness and single status. The COR group was characterised by a history of physical and sexual abuse, family history of addictions, more intrusive sexual offences and higher rates of offending. These results highlight different profiles for sexual offenders in forensic mental health and correctional settings and challenge us to consider the implications for assessment, treatment and risk management of this unique group of sexual offenders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".