Policy Design for Development Plan of the Saribu Rumah Gadang Tourism Area, Solok Selatan Regency, Indonesia
Bibliographic record
Abstract
This article focuses on the management development plan for the Saribu Rumah Gadang Tourism Area, Solok Selatan Regency, Indonesia.The research methods used in this study are the desk study method, participatory qualitative methods through focus group discussions (FGD), and direct observation methods at the research location.The results of this study illustrate several points, namely: governance analysis, analysis of the position of tourist areas in the RTRW document, Analysis of Zoning System, Accessibility Analysis, Internal Travel Pattern Analysis, Parking Management Analysis, Circulation Analysis, Pedestrian Analysis and Activity Actor Analysis and Facilities in the Saribu Rumah Gadang Tourism Area.The recommendation from this study is that the policy for managing the Saribu Rumah Gadang Tourism Area must involve active participation from the community, private sector, central, regional, and Nagari governments, which are very determining factors in encouraging and moving tourism in the Saribu Rumah Gadang Tourism Area to become a leading tourist destination, thereby providing benefits, which is bigger both from a historical, cultural and economic perspective.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.001 |
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".