Réflexions à partir d'une expérience universitaire de formations en sciences sociales dans le domaine du vieillissement
Bibliographic record
Abstract
Cet article rend compte d’une expérience de formations et de recherches dans le domaine du vieillissement, depuis plus de trente-cinq ans, et considère les mutations dans l’offre, la pédagogie et les publics d’étudiants. Définie au départ dans le cadre de la formation continue, la démarche pédagogique et scientifique allie les principes de l’éducation permanente, de la recherche-action coopérative et la visée d’une université ouverte sur différents publics et territoires. L’intégration d’étudiants de formation initiale influe dorénavant sur la mise en œuvre des orientations pédagogiques et, par ailleurs, la multiplication des masters professionnels conduit à des concurrences jouant sur la visibilité des compétences, des certifications professionnelles et des emplois. Cette situation est mise en comparaison avec celle de deux universités : Sherbrooke (Québec) et São Paulo (Brésil).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".