Regard sur la formation professionnelle au XXe siècle et repérage des problèmes de recherche pour le XXIe siècle
Bibliographic record
Abstract
Résumé: Domaine de recherche en émergence, la formation professionnelle au secondaire et la formation des enseignants de ce secteur s’enracinent fermement dans les changements qui ont marqué le marché du travail au cours du dernier siècle. Au Québec, au Canada, aux États-Unis, en Europe ou ailleurs, la formation professionnelle tend à suivre ou à subir les grands changements sociaux et politiques. Cette recension d’écrits s’attarde à jeter un regard rétrospectif sur l’évolution de ce domaine et de ces problèmes de recherche, ce qu’un survol des mots-clés principaux dans les banques de données vient illustrer. De plus, elle renverse la perspective pour identifier prospectivement des pistes de recherche fertiles pour les années à venir. Abstract : Recent research field, the vocational education and teacher training in this sector are deeply connected in the transformation that marked the labor market during the last century. In Quebec, Canada, USA, Europe or elsewhere, vocational education and training follows the major social and political changes. This literature review presents a look back on the evolution of this area and these research problems and an overview of the main keywords in the data banks illustrates this. Also, it reverses the perspective to identify prospectively relevant research directions for the coming years. Mots-clés: formation professionnelle, enseignement professionnel, historique, problèmes de recherche Keywords : Vocational education and training, teacher training, historical, research problems
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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 | 0.039 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.028 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".