Des analogies entre le raisonnement médical et l'évaluation formative
Bibliographic record
Abstract
La présente contribution examine l’hypothèse de la viabilité d’une analogie entre deux activités au cœur des actions respectives du médecin et du pédagogue, le raisonnement médical et l’évaluation formative des apprentissages. A partir de définitions élémentaires, les auteurs examinent d’abord en quoi le raisonnement médical et l’évaluation formative sont deux démarches cliniques, en soulignant les tensions épistémologiques que recouvre cette notion. Puis, sous la forme de rapprochements comparatifs, ils analysent successivement quelques similitudes ou distinctions à établir entre les deux activités, au regard de plusieurs attributs, notamment leurs objets, leurs processus et les postures qu’ils impliquent. Les analyses font essentiellement référence au raisonnement médical des médecins et l’évaluation formative est plus particulièrement considérée au regard de la manière selon laquelle elle est régulièrement mise en œuvre dans le cadre de la supervision formative en contexte clinique.
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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 | 0.002 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".