Bibliographic record
Abstract
Research indentifies that a significant proportion of youth within the justice system possess some form of mental health disorder, and that the presence of an emotional disorder can provide important explanatory value regarding the causes of crime.Evidence is now overwhelming that services within the youth justice system need to account for the causes of crime in order to effectively reduce the likelihood of reoffending.Such an ethic within youth justice service delivery not only reduces symptoms and risk within the youth and their families but also is linked to increasing community safety through reductions in reoffending.This review characterizes the relevance of mental health disorder in considering the needs of anti-social youth, and how this appreciation is linked to the delivery of effective services as well as what constitutes supportive youth justice legislation About the AuthorAlan Leschied, Phd, c Psych, is a psychologist and professor at the university of Western ontario, in london, ontario. he has been involved in children's services for over 30 years, providing assessment to the court and developing knowledge in the assessment and treatment of youth who are in conflict with their communities, involved in the child welfare or involved in the children's mental health systems.he can be contacted by phone at 519-661-2111, ext.
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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 | 0.001 | 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 | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".