Measuring Tourism Impacts on Community Well-being at the Hani Rice Terraces GIAHS Site, Yunnan Province of China
Bibliographic record
Abstract
To reflect the intricate relationships between heritage, tourism, and community pertinent to Globally Important Agricultural Heritage Systems (GIAHS), the framework of community well-being is adapted to evaluate the status and changes to destination communities imposed by conservation and tourism initiatives. A multi-stakeholder, mixed-method approach is adopted using qualitative interviews and a quantitative questionnaire survey at two villages of the Hani Rice Terraces, Yunnan Province of Western China. Results show that positive impacts from tourism are mainly concentrated on the environmental, conservation, and development dimensions. However, the lack of improvements in the education and health dimensions negatively affected the well-being of the local community. In particular, the subjective well-being is reduced with the increasing need for education induced by tourism. The evolution of community well-being is explored and portrayed through well-being hexagons and measures to enhance the positive impacts of tourism are proposed for GIAHS and other heritage sites or protected areas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".