Acceleration of Environmental Sustainability in Tourism Village
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The research aims to determine the factors causing the low achievement of environmental sustainability in tourist villages and accelerate it. This study uses a desk research method with online data and information search techniques, secondary sources, and other scientific publications. Meanwhile, the analysis technique used is a descriptive qualitative analysis technique, analogy, and comparison of several research results and other scientific publications related to environmental sustainability in tourism villages through the local wisdom approach and digital transformation. The research was conducted by interviewing several sources to get input on ecological sustainability standards in Tourism Villages. The result shows that the standards used to measure environmental sustainability in tourist villages can be used because of the global nature of the standards. Tourism Villages have local wisdom that has become part of the community's life. This local wisdom is very likely to have encouraged the tourism village community to behave environmentally friendly. Local wisdom becomes the focal point and main attraction of a tourist village that can be disseminated to villagers and tourists. The results of the study suggest the optimal way in which sustainable environmental development in the village can occur.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it