Une analyse didactique de pratiques pédagogiques en premier cycle universitaire d’histoire. Apprendre à lire historiquement en histoire ancienne
Bibliographic record
Abstract
L’article interroge les rapports entre pratique de recherche en histoire et enseignement en premier cycle universitaire, afin d’identifier les conditions didactiques de la logique de certains choix pédagogiques. L’étude du cas d’un cours en histoire de la Grèce ancienne sur l’ostracisme est menée selon une approche qualitative dans le cadre didactique de l’apprentissage par problématisation. Elle rapporte les énoncés écrits et oraux des étudiant⋅e⋅s (un groupe de 36) à leurs lectures et aux discours du professeur, selon certains enjeux épistémologiques et historiographiques de la recherche historique sur l’institution politique de l’ostracisme. L’analyse met en lumière un malentendu entre l’enseignant et les étudiant⋅e⋅s qui provient de l’invisibilité des divergences de configurations historiographiques (au sens de Prost, 2006) qui sous-tendent leurs approches respectives.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".