The Translation and Dissemination of Chinese Opera in the English-Speaking World
Bibliographic record
Abstract
This paper delves into the translation and dissemination of Chinese opera in the English - speaking world from 1919 to 1949. It examines the English translation and overseas dissemination of Chinese opera during this period, including the historical context, the status of foreign translation, and the characteristics of its dissemination in the UK and the US. The paper analyzes the implications for dissemination and proposes strategies to strengthen the overseas dissemination of Chinese opera, such as improving translation quality, expanding dissemination channels, and fostering diverse dissemination entities. Additionally, it is suggested to deepen the exploration of its intrinsic values, promote its innovative development on the international stage, and facilitate the mutual learning and exchange of Chinese and foreign cultures.The overseas dissemination of Chinese opera to the West started in 1731 with the French translation of The Orphan of Zhao. In the first half of the 20th century, globalization facilitated its spread. A batch of books on Chinese opera emerged, mainly by expatriates in China. The translations were mainly of Yuan zaju, with marriage and love plays and social case plays being popular. Many translations had low fidelity to the original text.In the UK, translations included plot introductions, selected and abridged translations, re - translations, and full translations. In the US, Chinese opera influenced local art forms. Mei Lanfang's US tour in 1930 was a great success, attracting wide attention.However, there are issues in the dissemination, such as a lack of unified translation methods. To promote the dissemination of Chinese opera in the English - speaking world, it is necessary to improve translation quality, expand and integrate dissemination channels, and cultivate synergy among multiple dissemination subjects. This will enhance China's cultural soft power and promote cultural exchanges.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".