Le rapport à la poésie d’enseignants du secondaire québécois : quelle progression entre les cycles/degrés ?
Bibliographic record
Abstract
Cette recherche vise à mieux connaitre les conceptions de la poésie des enseignant-e-s de français du secondaire québécois pour comprendre les finalités d’enseignement qu’ils y associent, ainsi que les objets, corpus et tâches qu’ils privilégient lorsqu’ils mettent en place des séquences ou des séances de poésie. Nous avons aussi analysé la progression au fil des cinq années d’enseignements de cet objet. Il s’avère que les enseignants prennent en compte la culture première des élèves, malgré le fait qu’ils partagent une vision traditionnelle et scolaire de la poésie, surtout à la fin de la scolarité obligatoire. Alors que la poésie n’a cessé d’évoluer au cours de l’histoire de la littérature, sa didactisation semble s’être peu adaptée aux transformations des genres poétiques.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".