Marcel, J.-F., Piot, T., & Tardif, M. (Dir.) (2022). 30 ans de politiques de professionnalisation des enseignants. Regards internationaux. Presses Universitaires du Midi. 306 p.
Bibliographic record
Abstract
du Midi.306 pages.Cet ouvrage intéressera sans doute d'abord les chercheuses et chercheurs oeuvrant dans le domaine de la formation à l'enseignement, même si on peut espérer que des personnes en formation voire des enseignantes et enseignants, s'emparent de tels travaux.Il aborde sous un angle original, en les reproblématisant, les enjeux complexes attachés à la (dé)professionnalisation de ce métier.Issus d'un symposium du Réseau international francophone de recherche en éducation et formation (REF) en 2019, les seize textes réunis (dont la préface de R. Etienne et la postface de C. Gervais) proposent des réflexions rétrospectives sur la période des 30 dernières années ancrées dans les différents contextes nationaux francophones (Belgique, France, Québec et Suisse), comme le veut la coutume de ce réseau, mais en y ajoutant cette fois une perspective brésilienne.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.017 |
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".