Avis de publication - Consolider la base de données probantes sur les inégalités en santé au Canada
Bibliographic record
Abstract
Promotion de la santé et prévention des maladies chroniques au Canada Recherche, politiques et pratiques Avis de publication Consolider la base de données probantes sur les inégalités en santé au Canada En mai 2018, l'Agence de la santé publique du Canada (ASPC) a publié le rapport intitulé Les principales inégalités en santé au Canada : un portrait national.Le rapport brosse un portrait statistique détaillé des inégalités ayant trait aux déterminants sociaux de la santé et aux résultats en matière de santé pour toute une gamme de groupes de population au Canada (p. ex.selon le revenu, le niveau de scolarité, la profession, l'indice de défavorisation matérielle et sociale, l'identité autochtone, l'orientation sexuelle et l'origine culturelle ou raciale).Ce rapport vise à renforcer la surveillance des inégalités en santé et à soutenir le développement de la recherche, des programmes et des politiques visant à améliorer l'équité en santé au Canada.
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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 | 0.016 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.026 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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".