L’écart entre la valorisation de la collaboration entre enseignant·e·s et la difficulté de sa mise en oeuvre formelle
Bibliographic record
Abstract
Cet article théorique montre la nécessité de tenir compte des conditions personnelles et structurelles pour mieux comprendre l’écart entre la valeur que les enseignant·e·s du primaire accordent à la collaboration en général et la difficulté de sa mise en oeuvre formelle. Une recension des écrits sur la collaboration entre enseignant·e·s, associée aux savoirs expérientiels de la principale chercheuse, nous amène à identifier des conditions de faisabilité. Cette collaboration prescrite par le ministère de l’Éducation du Québec (1997) est en lien avec l’augmentation du nombre d’élèves en difficulté. Pour favoriser leur réussite, une plus grande collaboration institutionnelle, professionnelle et pédagogique au sein des équipes-cycle s’avère nécessaire. Alors que la pertinence de la collaboration en général est bien documentée, de nombreux obstacles apparaissent dans sa mise en pratique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".