Le transfert des apprentissages en milieu organisationnel : réflexions, perspectives et nouvelle taxonomie
Bibliographic record
Abstract
Bien que le transfert des apprentissages représente un enjeu majeur en milieu organisationnel, il constitue également une préoccupation, certains chercheurs affirmant que pas plus de 10 % des activités de formation produisent des résultats. D’un point de vue théorique, la situation n’est pas non plus très claire. Alors que certains auteurs fondent le transfert sur la généralisation et le maintien des apprentissages, d’autres soulignent plutôt son caractère adaptatif. Cet article présente, au moyen d’une taxonomie, une vision différenciée du transfert des apprentissages qui met l’accent sur son caractère adaptatif et contextualisé, rendu nécessaire en raison d’environnements organisationnels en changement constant.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".