Enseigner le métier d’acteur·trice : expériences de formation du corps et approches privilégiées
Bibliographic record
Abstract
Cet article porte sur les stratégies et les approches axées sur le travail corporel privilégiées par cinq professeur·es (Francine Alepin, Martine Beaulne, Pascal Belleau, Huy Phong Doan et Mélanie Demers) dans le cadre de différents cours de voix, d’interprétation et de mouvement offerts à l’École supérieure de théâtre (ÉST) de l’Université du Québec à Montréal (UQAM). En m’appuyant sur la théorie de l’activité (Engeström, 2000), je tisse des liens entre les diverses composantes (sujet, objet, communauté, règles, division du travail, outils, finalité) associées à ces contextes de cours et j’approfondis leur finalité commune d’autorégulation vis-à-vis du travail du corps, un corps à la fois charnel, performant, personnifiant et en relation avec d’autres.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".