Harnessing community participation tourism development in Himalayan region of Uttarakhand State, India
Bibliographic record
Abstract
The article aims to evaluate the participation of below-poverty-line local community in tourism-related business activity in Himalayan state of Uttarakhand. Further, this article addressed for those who work in the tourism sector. The study employs a mix of methods, including survey data from 500 respondents with a random sampling approach, using Analysis of variance (ANOVA) statistical tools for analysis, other methods were interviews and observations at six tourism sites in Garhwal and four sites in Kumaun. Our findings showed that there has declined in community participation in tourism development, due to the lack of economic benefits obtained in the tourism sector, many believe that the tourism sector does not provide much income growth for them and does not make a significant contribution to the development of their region. Moreover, lack of understanding is considered the basis for community’s inability to play an active role, and lack of stakeholders’ involvement in encouraging them to improve their economy and culture through the tourism sector. Ultimately, this research also underlines the existence of some efforts by tourism travel to encourage public trust, which can help reduce poverty and increase community trust in tourism development in their region.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".