Au-delà des projets pilotes: la diffusion des innovations dans les services de santé
Bibliographic record
Abstract
Bien apres que Monique Begin eut remarque que le Canada etait un pays de projets pilotes (Begin et al. 2009), les leaders de la sante debattent encore sur les meilleures facons d'appliquer a plus grande echelle, de diffuser et de soutenir les innovations qui portent fruits. Cette question est l'un des plus grands defis – et par le fait meme une des plus grandes opportunites – pour les systemes de sante d'aujourd'hui. Parfois, les meilleures idees ne depassent pas l'etape du projet pilote et s'etiolent avec le temps, alors que leurs defenseurs passent a autre chose. En fait, l'idee derriere cet editorial m'est venue lors d'une reunion ou plusieurs leaders affirmaient que les innovations ne se propageaient jamais, qu'il etait pratiquement impossible d'apporter des changements a grande echelle dans les systemes de sante.
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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 | 0.086 | 0.271 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".