Study on Rural Revitalization in Hong Kong, China Based on the Concept of Eco-Museum: The Case of Yantianzi (Yim Tin Tsai)
Bibliographic record
Abstract
Eco-museum, as a sustainable model for maintaining the overall cultural, natural, and social landscape of protected areas, has been gradually applied to the rural revitalization vision in Hong Kong, China. In order to further explore the rural development of Hong Kong from an eco-museum perspective, this paper analyses and studies the process of rural revitalization based on theoretical analysis, with Yantianzi as a case study. The results show that although there are strengths in development potential, revitalization model, responsibility framework and social participation, there are also problems in areas of population, villagers' return and relic restoration and skills transmission, as well as a slow development process of the "growth model" of the eco-museum and a lack of industrial support. Hence, the Joint Committee, the villagers, the government and other relevant actors need to make improvements and adjustments accordingly. This paper provides feasible advice and enriches the research on eco-museums and rural revitalization with both theoretical and practical value.
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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 | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".