Sustainable Tourism Model in Pagilaran Tea Plantation Agrotourism, in Indonesia
Bibliographic record
Abstract
Sustainable development is a global agenda with issues of economic growth, environment, and welfare. The instrument for realizing sustainable development is through sustainable tourism. Agrotourism as an effort to apply the principles of sustainable tourism focusing on environmental, social, and economic dimensions. This study aims to find a sustainable tourism model in Pagilaran Tea Plantation Agrotourism. This study uses a qualitative method with a case study concept. The data collection techniques used in the study were observation, in-depth interviews, literature study, and documentation. The data were analyzed by source triangulation and the data were analyzed with the help of Atlas.ti.8 software. The result of this study was the model of sustainable tourism in Pagilaran Tea Plantation Agrotourism that involves social, economic, ecological, cultural, and educational dimensions. The novelty of this study is that the Sustainable Tourism model in Pagilaran Tea Plantation Agrotourism involves the University element and is committed to upholding the principles of Tri Dharma of Higher Education, namely Education, Research, and Community Service. Pagilaran Tea Plantation Agrotourism implements Pentahelix collaboration in realizing sustainable tourism by involving academics, companies, communities, government, and media. Pagilaran Tea Plantation Agrotourism is committed to being a vehicle for family tourism, the official tourism, and study tour by prioritizing edutourism and providing ecological insight. The tourism potentials such as Tea walking, Tea Factory, and tea picking dance become the uniqueness and attraction of Pagilaran Tea Plantation Agrotourism. The novelty result of this study is that the Educational dimension is an element that can strengthen the realization of Sustainable Tourism.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".