Sustainability of community-based mangrove ecotourism in Bali, Indonesi
Bibliographic record
Abstract
Bali is a world tourist destination that is famous for having various types of interesting maritime tourism, including mangrove areas which are typical of equatorial regions. The purpose of this study is to develop a model that can predict the sustainability of ecotourism in the mangrove area in Bali based on the approach of empowering local potential and empowering the community. Data analysis was carried out using Bayesian Network analysis, where input was based on the results of the FGD. The results show high probability of realizing the sustainability of ecotourism, where the most influential variables are community participation and local product developers or mangrove-based products. In addition, the condition of the mangrove forest also needs attention, considering that the sustainability of mangrove ecotourism is very sensitive to changes in the condition of the mangrove forest. The three main variables have reflected the combination of the three elements of sustainability, namely people-social (community participation), planet-environment (mangrove forest condition), and profit-economic (developing of mangrove-based products). Mangrove ecotourism development in Bali should be focused on increasing community participation and the development of mangrove-based products.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".