Formations pédagogiques musicales en Suisse. Des outils didactiques émergents
Bibliographic record
Abstract
La présente recherche, soutenue par le Fonds national suisse (fns), se consacre aux enseignements d’un groupe de didacticiens de la musique des Hautes écoles de musique (hem) de Genève, Lausanne, Bâle, Lugano et Berne. Ces enseignements sont appréhendés comme susceptibles d’éclairer les changements intervenus dans la formation des formateurs et la nature de l’évolution des dispositifs. Les modes de professionnalisation des futurs enseignants de musique en fin de formation sont au coeur de cet article. Nous présentons, dans les quatre parties de cet article : les spécificités de cette recherche, y compris sa méthodologie mixte (quantitative et qualitative), l’analyse qualitative de modèles professionnels sous-jacents aux pratiques des formateurs, le corps dans une double fonction (comme outil pour enseigner et comme objet d’enseignement), les rôles et jeux de rôles inhérents aux variations didactiques d’un professionnel de l’enseignement.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".