La gestion cognitive des connaissances dans les organisations
Bibliographic record
Abstract
Depuis les années 1990, le phénomène de la mondialisation s’est accéléré tandis qu’Internet et les nouvelles technologies de l’information et des communications (NTIC) ont accru considérablement la quantité d’informations à gérer. Or des recherches sur les dynamiques de traitement de l’information existent depuis plusieurs dizaines d’années en sciences cognitives et seraient très utiles en gestion des connaissances. Cet article présente un concept qui favorise la fertilisation de la gestion des connaissances par les sciences cognitives : la gestion cognitive des connaissances (GCC). La GCC vise à favoriser l’innovation, l’efficience, la communication, l’adaptation au changement, la prise de décision et la résolution de problèmes des organisations en tirant profit des connaissances de toutes leurs composantes.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".