Offenders on judicial orders: Implications for evidence-based risk management in policing
Bibliographic record
Abstract
There is little known about individuals who serve judicial protective orders called Section 810.1 and 810.2 peace bonds. Many Canadian police services provide supervision of these individuals, who are deemed high risk for violence, yet little research has been done on community supervision by police. The current study profiles the characteristics of 45 adult supervisees who were serving 810.1 and 810.2 orders and supervised by a local police service. The findings indicate that a majority of these individuals have experienced childhood abuse and neglect, lack high school education, were exposed to parental alcoholism, and demonstrated evidence of mental health problems. Further, and perhaps less surprising, they had remarkable histories for criminal behaviour, in terms of frequency, severity, and antisocial behaviour. Most of the individuals had criminogenic risk factors and responsivity issues that required attention at the start of their supervision. This study highlights the high needs of individuals under judicial orders and provides insight into the level of resources needed to supervise them. Implications for training law enforcement in applying effective principles of rehabilitation and risk assessment are 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 | 0.083 | 0.237 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".