The Role and Social Function of Maoqiang Chinese Opera in Transmitting Cultural Heritage through Education
Bibliographic record
Abstract
This research investigates the transmission of Maoqiang opera, focusing on the iconic repertoire “Zhao Meirong Guan Deng” and its role in preserving cultural heritage in the Shandong Peninsula. The objective is to investigate the role and social function of Maoqiang Chinese opera in transmitting cultural heritage through education. The research site encompasses various academic institutions and community-based events in Jiaozhou City, where key informants, including Maoqiang opera practitioners and local authorities, provide insights into the transmission process. Data analysis involves qualitative methods, including interviews, observations, and document analysis, to elucidate the multifaceted role of “Zhao Meirong Guan Deng” in cultural transmission. Methodologically, the research employs a mixed-methods approach to capture the complexity of Maoqiang opera transmission and its societal impact. The research results highlight the enduring legacy of Maoqiang opera and the effectiveness of incorporating traditional repertoire into educational curricula, fostering an appreciation for intangible cultural heritage among diverse audiences. Suggestions for future research include exploring innovative transmission strategies, leveraging digital media, and strengthening collaboration between cultural institutions and educational stakeholders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".