The effect of tourism village development project on economic sustainability through tourism villages based on natural and cultural potentials
Bibliographic record
Abstract
Tourism village development projects have become attractive to the community during the Covid 19 Pandemic and after. This condition is caused by many people in urban areas who wish to travel to natural and indigenous cultural destinations. Tourism village development is a process that emphasizes ways to develop or advance tourist villages. Village green tourism development projects through natural and cultural destinations are expected to provide sustainable village economic sustainability. The distribution of questionnaires to obtain the potential for village tourism development was determined by the project team that will develop in identifying, assigned consultants and key people from local villages, including leaders with a total of 46 respondents. Data processing looks at the relationship between village economic sustainability and village economic sustainability through natural and cultural tourism potential using partial least squares. The data processing results show that the village tourism development project has a positive effect on nature tourism potential, cultural tourism potential, and village economic sustainability by increasing the welfare of local communities. The nature tourism potential of the village, which has attractive mountains and a reliable source of agricultural products, is capable of impacting the local community's interest. Cultural tourism potential owned by the village with attractive tourist performances on a regular and well-scheduled basis and the ability of the village to show dance performances that reveal their identity can impact the village's economic sustainability. The village green tourism development project is set in the finalization stage of project planning by considering the project completion time.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".