Le synopsis : un outil méthodologique pour comprendre la pratique enseignante
Bibliographic record
Abstract
L’article présente l’adaptation d’un outil méthodologique spécialisé, le synopsis, mis au point par le Groupe romand d’analyse du français enseigné (GRAFE), en Suisse. Conçu pour traiter et concentrer des données filmées en vue de décrire et comprendre des objets enseignés en classe de français, le synopsis a été adapté pour décrire et comprendre les pratiques enseignantes entourant les tâches de lecture et d’écriture en classe de science et d’histoire à l’école secondaire, au Québec. Le glissement de focus de l’objet enseigné vers les pratiques enseignantes a imposé des ajustements importants qui se justifient par la nécessité d’adéquation entre les outils et les objets de recherche.
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 | 0.029 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".