Heritage Tourism in a Historic Town in China: Opportunities and Challenges
Bibliographic record
Abstract
Heritage tourism is a driver of economic growth in many historic towns. However, these places often experience many problems and current planning usually does not address all the difficulties adequately. Small towns in peripheral areas often lack economic opportunities and rely heavily on cultural heritage to develop tourism. A conceptual framework was applied to examine the challenges and opportunities of heritage tourism development in a small historic town in Guangxi, China, based upon semi-structured interviews with decision makers, business operators and residents, supplemented by on-site observations and review of secondary data. Findings reveal that tourism provides incomes, fuels local economic development and increases awareness and knowledge of cultural heritage, but also brings changes to the town, presenting challenges to the community and heritage perpetuation. Stakeholders differ in the power that they bring to bear, and also in the positions that they hold on tourism development and heritage conservation. Insufficient financial resources and lack of adequate planning and effective management are impediments to heritage tourism. Adaptive planning, with broader community participation and greater collaboration among stakeholders, is proposed to achieve more equitable development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".