Guides visant à faciliter la mise en oeuvre et l’évaluation de la prescription sociale : leçons tirées du modèle « Accès aux ressources communautaires »
Bibliographic record
Abstract
Résumé La prescription sociale est une approche globale qui agit sur les déterminants sociaux de la santé. « Accès aux ressources communautaires » (ARC) est un programme de prescription sociale novateur aux services bilingues qui offre un point d’entrée unique pour les besoins en matière de santé et de services sociaux et qui permet d’apporter des changements dans les lieux de pratique dans le but d’aider les fournisseurs de soins primaires à mobiliser leurs patients, grâce à un intervenant-pivot non clinicien qui aide les patients à accéder aux ressources communautaires pertinentes. L’équipe du programme ARC a créé une trousse d’outils de prescription sociale qui contient des conseils pratiques sur l’établissement, la mise en oeuvre et l’évaluation de programmes de prescription sociale ainsi que sur le suivi des progrès. Les quatre guides du programme ARC sont facilement adaptables à divers milieux de pratique et de recherche.
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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 | 0.064 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".