Vers des solidarités numériques en éducation : possibles champs d’action
Bibliographic record
Abstract
Ce numéro thématique fait suite au colloque ROC 2021 sur le thème « Solidarités numériques en éducation : une culture en émergence ». Une volonté partagée de baliser le « territoire de questionnement » (Bouchard, 2011) des solidarités numériques au service de l’apprentissage a émergé des présentations et des échanges qui ont eu lieu. La communauté des chercheurs et celle des praticiens rendent ainsi compte d’initiatives de solidarités numériques au service de l’enseignement et de l’apprentissage dans les contextes de réponse aux enjeux de « continuité pédagogique » ainsi que du rôle des acteurs. Au-delà des limites inhérentes à ce vaste chantier, les dix contributions de ce numéro traduisent de possibles champs d’action au service du développement d’une culture de solidarité numérique en éducation.
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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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.029 | 0.021 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.016 | 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".