Are Dangerous Offenders Different From Other Offenders? A Clinical Profile
Bibliographic record
Abstract
The Canadian dangerous offender (DO) statute requires the assistance of psychiatrists and psychologists in evaluating offenders' potential danger and risk of future offenses, without substantive supporting empirical clinical research on the topic. The present study compared 62 men facing Canadian DO applications to 2,414 non-DO sexual and violent offenders (ACs) and 62 non-DO offenders matched on offense type (MCs). DOs differed significantly from ACs on 30 of 45 variables and from MCs only on 6. More DOs than MCs had an extensive criminal history, were psychopaths, and had more school truancy. Compared with ACs, DOs had less education and more school adjustment problems, more disturbed childhoods, and more often were diagnosed with sadism, psychopathy, and substance abuse problems. Total sexual and violent offense convictions provided the best but weak distinction of DOs from ACs. The "three strikes" law is noted and early intervention in DOs' criminal careers is discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".