Implementation Model of Community Based Tourism on Rural Tourism
Bibliographic record
Abstract
One effort of increasing rural economy can be conducted by developing rural tourism. Tourism sector is considered to be capable to encourage the development of other economy sectors. Tourism also contributes in increasing job opportunity and income. The bottom up planning paradigm expects the community to take roles as both subject and object of development. Dieng Plateau as a tourist attraction has various kinds of attractions. Rural tourism is designed by the local community to the tourist attraction in Dieng. This research aims at identifying how the implementation model of Community Based Tourism has been conducted to the development of Dieng Kulon rural tourism. This research is a qualitative one, which uses the primary data taken from Observation Technique and Focus Group Discussion. The analysis used in this research is descriptive qualitative and Participatory Rural Appraisal (PRA). This research has found a model of Community-Based Tourism that has been conducted in the development of Dieng Kulon rural tourism through Pokdarwis (Tourism Awareness Group) and Pokja (Workgroup) establishment on eight fields. The Community Based Tourism model that has been tested and implemented in this research may complement the models in the previous research findings, which show the roles and functions of each actor of tourism development.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".