The Moscow Version of the Opera “Marriages Samnites” by A.-E.-M. Grétry
Bibliographic record
Abstract
О ярком феномене театральной жизни Москвы последней четверти XVIII века, французской опере с разговорными диалогами в переводе на русских язык, свидетельствует уникальный памятник — рукописные материалы первых двух действий русской версии оперы А.-Э.-М. Гретри «Браки самнитян» в фонде Письменных источников Московского музея-усадьбы Останкино. При всем стремлении представить спектакль «как во Франции» почти каждое произведение в переводе на русский язык преображалось. Особенно показателен пример «Браков самнитян». В статье проводится подробное сравнение московской («шереметевской») версии оперы с ее французскими редакциями. French opera with spoken dialogues translated into Russian was a bright phenomenon of Moscow musical life of the last quarter of the 18th century. In this article a unique monument of it is examined: manuscript materials of the first two acts of the Russian version of the opera “Marriages Samnites” by A.-E.-M. Grétry, which has been preserved in the Foundation of Written Sources of the Moscow Museum-Estate Ostankino. In spite of the desire to present the play “as in France” almost every work translated into Russian has been transformed in some way. An example of “Marriages Samnites” is particularly illustrative in this regard. In the article a detailed comparison of the Moscow version of this opera with its French redactions is carried out.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".