‘Traditional’ opera in a ‘modern’ society: institutional change in Taiwanese<i>xiqu</i>education
Bibliographic record
Abstract
All discourses of modernisation in the twentieth century Sinophone world engaged Western, Soviet and Japanese influences and models, and traditional Chinese theatre education was no exception. Although the Republic of China on Taiwan never confined theatre to state-sponsored organisations, a system of theatre education was created to ensure continuity of Jingju (i.e. ‘Peking opera’) performance, officially identified as the ‘national theatre’. Beginning with the 1957 establishment of a private vocational school, Jingju education adopted various (Western-inspired) models, moving from professional training colleges to the present single national post-secondary institution, the 12-year (elementary, secondary and post-secondary) National Taiwan College of Performing Arts (NTCPA). Since nationalisation in 1968, the school has featured in public debate surrounding the place of traditional theatre in Taiwan’s shifting cultural politics. Its curriculum and training methods notably came under scrutiny by a legislator in 1970, who found that the school was in desperate need of ‘modernisation’ to conform to education standards. Yet since actor technique is acquired through kinship-like student‒teacher relations, the adaptation of oral teaching to ‘Western’ and ‘modern’ ideas of education, as well as to an academic calendar, remains problematic and contested, with far-reaching implications for theatre performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".