L’enseignement de la statistique en Staps : l’ouvrage pédagogique
Bibliographic record
Abstract
Les Sciences et Techniques des Activités Physiques et Sportives (Staps) constituent la section 74 du Conseil National des Universités (CNU). Regroupant un ensemble de formations pluridisciplinaires centrées sur la motricité humaine, l’activité physique et le sport, les Staps sont également un vaste champ de recherche connecté à de nombreuses autres sections du CNU (histoire, sociologie, psychologie, biologie, physiologie, etc.). Cataloguée généralement dans les « outils (du travail universitaires) », la statistique n’a encore qu’une place relativement confidentielle dans cet écosystème. Pourtant, les nombreuses spécificités de l’objet « sport » sont propices au développement de modélisations et d’approches statistiques propres. Dans cet article nous proposons de revenir sur l’enseignement d’une statistique très « Staps » à destination d’étudiants de licence, master et doctorat. C’est au regard de l’évolution de trois ouvrages pédagogiques produits depuis les années 1990 que nous interrogeons la place de la statistique en Staps aujourd’hui.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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; 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".