Les tournées du Ballet de l’Opéra de Paris au temps de Lifar (1930-1958)
Bibliographic record
Abstract
Pendant les trois décennies qui correspondent au mandat de maître de ballet de Serge Lifar à l’Opéra de Paris, la mobilité de la compagnie ne cesse de se développer dans les pays limitrophes comme dans les pays lointains. Dans le contexte de la Seconde Guerre mondiale et de l’après-guerre, le Ballet du Théâtre national de l’Opéra de Paris tient de plus en plus le rôle d’ambassadeur culturel. Seules les tournées au long cours sont évoquées dans cette étude. Après l’Espagne en 1940, les États-Unis et le Canada en 1948, le Brésil et l’Argentine en 1950, la tournée à Moscou en 1958 conclut le mandat du chorégraphe ukrainien. La programmation et la réception des œuvres, connues de façon parcellaire, permettent de comprendre les enjeux esthétiques et identitaires d’une troupe qui suscite un vif intérêt.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".