La mobilisation des connaissances issues de la recherche dans l’accompagnement du développement professionnel
Bibliographic record
Abstract
Le mentorat, le coaching et toute autre forme semblable d’accompagnement du développement professionnel ont comme objectif, entre autres, d’aider le professionnel à mobiliser des connaissances issues de la recherche dans l’amélioration de ses pratiques. Grâce à une recension des écrits, la recherche présentée dans cet article a permis une clarification conceptuelle, notamment sur les termes connaissances, transfert et mobilisation. Elle a aussi mis en lumière les conditions favorables à cette mobilisation. Il s’agit principalement de repérer les connaissances pertinentes, notamment celles qui sont en lien avec la pratique professionnelle, et d’intégrer ces connaissances au processus réflexif et décisionnel inhérent à toute pratique professionnelle. En amont de la mobilisation, la qualité du dialogue entre les chercheurs et les professionnels a un impact – positif ou négatif – sur les retombées de la recherche dans l’expérience quotidienne des praticiens.
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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 | 0.062 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 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".