Santé mentale chez les francophones en situation linguistique minoritaire
Bibliographic record
Abstract
Bien que la plupart des études considèrent l’importance des déterminants sociaux sur l’existence des troubles mentaux, aucune ne désagrège les données en fonction de l’appartenance à une communauté de langue officielle en situation minoritaire, un fait pourtant reconnu pouvant avoir un impact sur la santé. L’incidence des langues et de la communication sur l’accès, la qualité et la sécurité des soins acquiert une portée plus grande dans le contexte canadien où coexistent deux langues officielles. Nous partons de cette prémisse pour dresser ici le portrait de la santé mentale de la population francophone vivant en situation linguistique minoritaire à partir des données de l’Enquête de santé dans les collectivités canadiennes — Santé mentale (ESCC, 2012) 1 .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".