Approche interdisciplinaire du geste musical : nouvelles perspectives en ethnomusicologie
Bibliographic record
Abstract
Cet article propose une réflexion épistémologique et méthodologique sur l’utilisation des nouvelles technologies pour l’analyse du geste instrumental en ethnomusicologie. Après un état des lieux des études sur le geste, nous montrons la nécessité de développer de nouveaux protocoles de collecte et d’analyse du geste instrumental sur le terrain. A partir de trois études de cas réalisées au sein du programme Geste-Acoustique-Musique de Sorbonne-Universités (luths d’Iran et d’Asie centrale, harpes du Gabon, xylophones et tambours du Cameroun, de France et du Canada), nous illustrons ce que nous permettent ces nouvelles technologies dans l’expérimentation et l’interaction avec les musiciens pour mieux comprendre le rôle de chacun des paramètres constitutifs du jeu instrumental et accéder notamment aux phénomènes de corporalité musicale. En conclusion, nous proposons quelques pistes de réflexion suscitées par ces technologies de capture du mouvement pour l’ethnomusicologie.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.026 | 0.023 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".