An examination of the risk management of high-risk sex offenders under a section 810.1 or 810.2 order in British Columbia, Canada
Bibliographic record
Abstract
Recognizance orders obtained under Sections 810.1 (sexual offences against children) and 810.2 (serious personal injury offence) of the Cnminal Code have been increasingly used to supervise warrant-expiry sex offenders in the community.However, the challenges of supervising these offenders remain virtually uncanvassed in the literature.This study seeks to address that gap by examining the challenges associated with the risk management of sex offenders under 810 orders in British Columbia.Qualitative data from seventeen interviews with criminal justice practitioners involved in the case management of these offenders were analyzed.Content analysis revealed that sex offenders under 810 orders are multi-risk, multi-needs, and require multi-interventions, which are often inadequately resourced or inaccessible in the community.The general unavailability of resources to address their multi-needs creates constraints on case management and reintegration.A difficult reintegration process may destabilize their risk factors, creating high-risk situations to reoffend.Implications of these findings are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".