De l’histoire et de l’avenir de la formation des maîtres au Canada anglais
Bibliographic record
Abstract
Au Canada, la formation des enseignants traverse une période riche en réformes. Toutefois, la plupart de ces efforts piétinent complètement ou n’ont qu’un faible impact. Nous soutenons ici que cette situation découle d’une absence de perspectives historiques. Nous analysons l’histoire de la formation des enseignants au Canada anglais, en montrant comment les diverses institutions de formation des enseignants qui se sont succédé se sont systématiquement approprié le pouvoir social d’autorités traditionnelles. Cette analyse sociale de la tradition oriente notre attention sur les interrelations entre les institutions, les rôles sociaux, le pouvoir et les connaissances. En explorant ces interrelations, nous montrons comment les formateurs d’enseignants, sur le plan individuel et collectif, et les forces historiques sociales plus élargies entrent en complicité pour maintenir le statu quo. Nous concluons en avançant que les formateurs d’enseignants ne peuvent devenir des agents de changement social plus efficaces qu’en réexaminant la manière dont ils se situent au plan socio-historique et en articulant de manière discursive la nouvelle autorité basée sur l’habileté plutôt qu’en récapitulant de manière compulsive les structures traditionnelles de pouvoir.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".