Inventaire des profils et des spécialisations des professeurs évoluant au sein des facultés ou des départements des sciences de l’éducation au Québec
Bibliographic record
Abstract
Cette étude examine les profils et les spécialisations des professeurs en sciences de l’éducation au Québec. Après analyse de leurs formations et de leurs domaines de recherche, les résultats révèlent une diminution de la diversité disciplinaire pour les trois cycles d’étude (baccalauréat au doctorat) et une prédominance croissante des spécialisations liées aux sciences de l’éducation. Ces spécialisations se concentrent sur l’enseignement, l’apprentissage et le développement professionnel au détriment des fondements de l’éducation (philosophie, histoire, sociologie). Cette tendance reflète un changement de paradigme, le passage d’une approche humaniste à une formation professionnalisante axée sur les pratiques du monde du travail. L’étude remet en question l’équilibre entre la formation pratique et théorique et suggère de consolider les fondements de l’éducation pour répondre aux exigences du nouveau référentiel des compétences professionnelles.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this metaresearch. It is in the settled core of the field.
Inventory of the training profiles and research specializations of professors in Quebec faculties of education, documenting shrinking disciplinary diversity and a shift away from the foundations; the object is the composition of an academic research workforce in Canada.
The primary object is the Canadian research workforce, including professors' training, research fields, and specialization patterns.
Inventory of Québec education-faculty professors’ profiles and research specializations; research workforce as object.
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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".