Bibliographic record
Abstract
Dans le numéro 10 de Recherches en danse, « Observer, analyser et dire le geste dansé », l’article de Nicole Harbonnier, Geneviève Dussault et Catherine Ferri présente le résultat de leurs recherches dans le domaine de l’analyse qualitative du mouvement introduisant une nouvelle proposition conceptuelle qu’elles ont nommée Observation-Analyse du Mouvement (OAM). En écho à cette nouvelle proposition conceptuelle sur l’analyse qualitative du mouvement, cet article tente d’illustrer, au moyen d’une exemplification concrète, l’une des multiples applications possibles de l’approche OAM. Je propose une analyse comparative de deux danseuses qui interprètent le même rôle féminin principal dans l’œuvre Carmen du chorégraphe Mats Ek. L’objectif de cette analyse vise à identifier les paramètres et les facteurs qui distinguent ces deux interprétations pour ainsi tenter de mieux comprendre comment chacune des interprètes a construit l’expressivité de sa propre Carmen à partir de l’idée que le chorégraphe avait lui-même du personnage.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".