Entre les bons et les méchants, entre le texte et la danse : La belle au bois dormant selon Perrault, Petipa, Ek et Lock
Bibliographic record
Abstract
Les rapprochements à faire entre l’univers du ballet classique et celui de la littérature sont nombreux, car cet art du mouvement puise souvent son inspiration d’œuvres littéraires. Mais comment s’effectue cette transposition du textuel au gestuel ? Comment narre-t-on à travers le mouvement ? En prenant La belle au bois dormant à l’appui, nous chercherons dans cet article à examiner ce lien intermédial, en comparant dans un premier temps, le conte de fées de Charles Perrault (1697) au libretto d’Ivan Vsevolozhsky (1890) ainsi qu’au ballet de Marius Petipa (1890). Dans un deuxième temps, nous analyserons comment les chorégraphies contemporaines de Mats Ek et d’Édouard Lock – Sleeping Beauty (1996) et Amjad (2007) respectivement – font des clins d’œil à l’œuvre de Petipa et ce que dévoile ce deuxième degré de transposition – du classique au contemporain – pour le rapport entre le texte et la danse. Ces études comparatives révéleront notamment que l’archétype peut être un outil important pour la mise en mouvement d’un texte.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".