Soutenir le développement professionnel d’intervenant.e.s école-famille-communauté en milieu défavorisé montréalais : faire dialoguer pratique, accompagnement et recherche
Bibliographic record
Abstract
Une école montréalaise pour tous (UÉMPT) est un programme ministériel dont la mission est de contribuer à la réussite éducative de tous les élèves issu.e.s des milieux défavorisés montréalais. Depuis 2021, nous animons un groupe de codéveloppement à l’intérieur duquel des personnes intervenantes école-famille-communauté (IÉFC), des ressources professionnelles d’UÉMPT et une chercheuse universitaire interrogent les contours du rôle d’IÉFC et les manières dont il se déploie spécifiquement en contexte défavorisé montréalais. Dans cet article, nous mettrons en lumière comment, en faisant dialoguer pratique, accompagnement et recherche, nous considérons soutenir le développement professionnel des personnes participantes.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".