Diversion, Conferencing, and Extrajudicial Measures for Adolescent Offenders
Bibliographic record
Abstract
In responding to youth crime, Canada makes disproportionate use of courts and custodial sentences, while other countries divert more youth from the formal justice system and make greater use of community-based responses. This article surveys diversion from the youth courts under the different youth justice regimes that have existed in Canada, including informal and formal screening, police and Crown cautions, and use of youth justice committees and conferencing. The newly enacted Youth Criminal Justice Act is intended to encourage greater use of these diversionary "extrajudicial measures," and more use of a "restorative justice " approach to cases. A major limitation is that these provisions are permissive, and create no new legal rights for youths and impose no new obligations on governments. It will be up to provincial governments to decide whether to allow police, prosecutors and local program operators to actually implement these provisions. Further, depending on how these provisions are implemented, there are legitimate concerns about the potential for these informal responses to abuse the rights of youths or ignore the needs of victims. There should be both monitoring of the implementation of these provisions and research to determine how effective they are at reducing offending, and meeting the needs of victims, offenders and communities.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 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".