Local Community Empowerment for Sustainable Tourism Development: A Case Study of Edelweiss Park Wonokitri Village
Bibliographic record
Abstract
Prior studies in sustainable tourism development have acknowledged gaps in our understanding of its various aspects-including environmental, social, and economic impacts-and the strategies for its effective implementation and long-term sustainability, particularly concerning the practical, step-by-step execution.This research aims to explore how empowering the local community can enhance tourist attractions, create memorable experiences, and increase visitor satisfaction, ultimately contributing to the sustainable development of the tourism village.Six informants were chosen based on their knowledge of the practice of sustainable tourism in Wonokitri village.The researchers considered six informants to be sufficient because they represent the key stakeholders involved in sustainable tourism practices that focus on local empowerment in Wonokitri village.The data was manually analyzed using a six-step data analysis process.This study's findings underscore that, beyond economic advantages, the local community garners social benefits through cultural preservation and environmental conservation, aligning with the goals of sustainable development.The collaborative efforts involving the government, private sector, and the engaged local community at Edelweiss Park exemplify how empowering the local community can foster tourism practices that yield comprehensive benefits for both the environment and the socio-economic well-being of the community.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".