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Record W2604234222 · doi:10.1080/19443927.2016.1240100

‘Traditional’ opera in a ‘modern’ society: institutional change in Taiwanese<i>xiqu</i>education

2017· article· en· W2604234222 on OpenAlexfundno aff
Josh Stenberg, Hsin-hsin Tsai

Bibliographic record

VenueJournal of Theatre Dance and Performance Training · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsModernization theoryScrutinyVocational educationCurriculumPolitical scienceSociologyPublic administrationPedagogyMedia studiesLaw

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.132
GPT teacher head0.292
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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