Mental Health in the Attention Models for Juvenile Offenders. The Cases of Colombia, Argentina, United States and Canada
Bibliographic record
Abstract
Abstract Objective: To investigate how mental health is understood and approached in the attention models of detention centers for the convicted underage population in Argentina, Colombia, United States and Canada. Methodology: A literature search was conducted using the following key words: adolescence, mental health, juvenile justice, juvenile delinquency, risk factors, and interventions. Searches were done through the search engine Pubmed. Additionally, public institution websites for each country were consulted. Conclusions: Juvenile delinquency is now understood as a multi-factorial phenomenon with multiple areas of intervention within which economic, domestic and social factors are considered relevant, since these favor the development of criminal behavior. A similarity was found between Colombian and Argentinian systems; both are based on restorative justice that seeks reparation and not punishment; which is why there are no punitive measures. When comparing Canada and the United States, it can be seen that Canada is more similar to Latin-American countries than to the United States, given that the latter uses punitive measures focused on the offender.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".