Se former pour éduquer : la spatialité comme ressource(s). Exercices de pensée critique géographique d’étudiantes et d’étudiants
Bibliographic record
Abstract
La question posée dans cet article est de savoir si les étudiantes et les étudiants qui se forment pour enseigner la discipline scolaire appelée, en France, « histoire-géographie » ont une appréhension particulière de leur futur métier d’enseignant en raison même de leur discipline de formation et d’exercice professionnel. Les savoirs disciplinaires leur servent-ils de ressources professionnelles? L’étude d’un corpus de portfolios de formation et d’évaluation d’étudiantes et d’étudiants se préparant à l’exercice du métier montre des usages différenciés de la spatialité. L’article expose une grille d’analyse qui permet d’identifier les mobilisations disciplinaires et les conditions d’un exercice de pensée réflexive et critique à fort enjeu éducatif.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".