Bibliographic record
Abstract
Dans le cadre de cet article, le processus d’implémentation, d’institutionnalisation et de systématisation d’un dispositif de coenseignement inclusif sera analysé par l’étude de cas d’une école secondaire québécoise. Cette école a systématisé graduellement un coenseignement total dans toutes les classes de 1re et 2e secondaire (en français, mathématiques et anglais) en réorganisant les ressources et en réorientant la population d’élèves en difficulté d’apprentissage et/ou d’adaptation (concentration des heures d’enseignement ressource, fermeture de classes spéciales, fin de la co-intervention externe, etc.). S’appuyant sur des observations en classe, des entretiens semi-directifs avec le personnel enseignant et la direction et des groupes de discussion réalisés avec l’équipe-école, cet article se penche ainsi sur le processus inclusif en l’analysant à partir des dix conditions de l’École inclusive (Tremblay, 2020).
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".