Negotiating Tradition and Innovation: Digital Heritage Practices and Cultural Sustainability of Suzhou Pingtan in Contemporary China
Bibliographic record
Abstract
As a traditional Chinese narrative-singing art, Suzhou Pingtan is encountering growing challenges of preservation and renewal due to population aging and technological shifts. The Pingtan community’s heritage inheritance and cultural identity are being impacted by the digital transformation, underscoring the conflict between cultural preservation and adaptable solutions. Using qualitative field observations, interviews with heritage practitioners and stakeholders, and document analysis, this study argues that online platforms have expanded access to heritage, involving the younger generation and offering economic opportunities. Traditional performances and digital media with an entertainment focus are deeply at odds because of concerns about digital literacy and language authenticity. The “Traditional Music Ecosystem Model in Digital Transformation,” which is put forth in this article, sees cultural sustainability as dynamic adaptation as opposed to static preservation. For sustainable heritage development, digital platforms, practitioner communities, and cultural institutions must have a strategic relationship. Through the application of research findings to globally endangered cultural practices, this study contributes to the theoretical understanding of heritage sustainability in the digital media environment.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".