Applying Media and Virtual Approaches to the Institutionalization of Puzhou Opera
Bibliographic record
Abstract
Puzhou opera, also known as Puju, originated in Puzhou in ancient China, which is now renamed as Yuncheng city, Shanxi province. Puju has been recorded since the Yuan dynasty and has become one of China’s most important operas because of its long history and influence on surrounding opera styles. This article explores challenges related to the institutionalization of Puju and how to use the modern technology of virtual media to ensure the sustainable development of traditional opera. In addition, as an insider of Yuncheng University, the researcher explored the application process of virtual media in promoting the institutionalized development of Puju and how to realize the learning, preservation, and inheritance of education and modern technology. To summarize, this study investigates the existing problems and challenges in using this virtual and media approaches and applies the media through virtual approach in the institutionalization of Puju to expand audiences and provide a new dissemination of opportunities.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.008 | 0.006 |
| 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".