Altérité et inclusion. Du corps propre au corps social en classe de langue : emprunts à la danse contemporaine
Bibliographic record
Abstract
La classe de langue étrangère, par la transformation du corps propre qu’elle présuppose afin d’accéder à un nouveau corps social, place-t-elle l’élève en situation de handicap et génère-t-elle de la souffrance ? Est-il possible de l’éviter ? La réflexion menée part de l’observation d’expériences vécues en danse contemporaine autour de la création de performances incluant des danseurs en situation de handicap. L’analyse de la démarche pédagogique adoptée fait émerger des constantes qui contribuent à l’inclusion de chaque danseur. Elle peut être source d’inspiration pour l’enseignant afin de construire une dynamique d’apprentissage d’une langue étrangère où chaque élève se sente compétent. Otherness and inclusion. What can contemporary dance bring to the foreign language class for learners to access a new social body? The foreign language class implies a transformation of the learner’s own body in order to access a new social body. Does it thereby handicap pupils, generating suffering? Is it possible to avoid this? The following reflection starts from the observation of experiences in contemporary dance, related to the creation of performances including disabled dancers. The analysis of the pedagogy reveals constants which contribute to the inclusion of every dancer. It can inspire teachers in order to design a foreign language learning approach in which each pupil feels competent.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".