Transfert de connaissances issues de la recherche en éducation : situation globale, défis et perspectives
Bibliographic record
Abstract
Le transfert des connaissances issues de la recherche s’impose comme un champ d’investigation incontournable dans plusieurs domaines. Tant en santé, en sciences sociales, humaines et appliquées qu’en éducation ou en gestion, des recherches visent à réduire le fossé entre les connaissances produites et ce qui est observé dans la pratique. Découlant d’une recension des écrits publiés entre 2007 et 2013, le présent article propose de situer le transfert des connaissances en éducation au regard de ce qui se passe globalement dans les autres domaines. Il en aborde les distinctions ainsi que les défis et les perspectives.
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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 | 0.092 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.012 | 0.082 |
| Scholarly communication | 0.038 | 0.027 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".