Applying a Health Development Lens to Canada’s Youth Justice Minimum Age Law
Bibliographic record
Abstract
OBJECTIVES: We applied a Life Course Health Development (LCHD) framework to examine experts' views on Canada's youth justice minimum age law of 12, which excludes children aged 11 and under from the youth justice system. METHODS: We interviewed 21 experts across Canada to understand their views on Canada's youth justice minimum age of 12. The 7 principles of the LCHD model (health development, unfolding, complexity, timing, plasticity, thriving, harmony) were used as a guiding framework for qualitative data analysis to understand the extent to which Canada's approach aligns with developmental science. RESULTS: Although the LCHD framework was not directly discussed in the interviews, the 7 LCHD framework concepts emerged in the analyses and correlated with 7 justice principles, which we refer to as "LCHD Child Justice Principles." Child involvement in the youth justice system was considered to be developmentally inappropriate, with alternative systems and approaches regarded as better suited to support children and address root causes of disruptive behaviors, so that all children could reach their potential and thrive. CONCLUSIONS: Canada's approach to its minimum age law aligns with the LCHD framework, indicating that Canada's approach adheres to concepts of developmental science. Intentionally applying LCHD-based interventions may be useful in reducing law enforcement contact of adolescents in Canada, and of children and adolescents in the United States, which currently lacks a minimum age law.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".