Quand la délocalisation numérique d’une partie d’un dispositif d’apprentissage permet de recentrer le temps présentiel sur un obstacle : exemple de l’appropriation de la courbe de Gauss par la manipulation d’objets concrets
Bibliographic record
Abstract
Les biostatistiques traitent les observations numériques réalisées sur le vivant. La référence à un modèle, telle la gaussienne, objet de cet article, représente pour notre public cible un obstacle épistémologique lié à son inaptitude à la modélisation mathématique. Les ostensifs graphiques interactifs sur lesquels repose notre dispositif didactique développé sur le Web lui restant encore peu accessibles, leur appropriation est assurée par la mesure d’objets et la transposition des données réelles d’un tableur en histogrammes concrets. Cette approche pratique n’a pu être mise en place que par la libération de temps didactique, inhérente à la délocalisation numérique d’une partie du dispositif original.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".