Rural Tourism as a Transformative Service of Community Well-Being: A Systematic Literature Review
Bibliographic record
Abstract
This study aims to look at the pattern and focus of rural tourism research over the last two decades. How much current research on rural tourism has centered on the position of rural tourism as a transformative service industry, in particular. A rigorous search is conducted in the current scientific literature databases, integrating narrative review and bibliometric research, to evaluate this correlation as well as to assess the effect of rural tourism growth on the various actors in the ecosystem (i.e., local population, local service providers, local authorities, tourists). It also includes a narrative study of clusters of topics under the headings of rural tourism and community well-being. We conducted a systematic thematic and material study of our chosen literature in addition to bibliometric analysis. Finally, a critical analysis of the methodologies used in the field of rural tourism is conducted. Since the connection between tourism growth and local TSR is still being researched, this study uses well-being (and other related terms) as an inclusion criterion for all types of tourism in rural areas. The report also aims to assess research progress on terms related to rural tourism, such as eco-tourism, nature tourism, adventure tourism, and community-based tourism, from 2010 to 2020. Furthermore, the study examines the relationship between rural tourism and well-being before and after 2010. The choice of 2010 as the turning point reflects the fact that after 2010, the relation between TSR (or wellbeing) and rural tourism becomes more visible. By using title, citations, publication journal and year, author information, keywords (name, countries, and institutions analysis), and author information, this search provides us with an aesthetic nature of our research. This paper set an agenda for future research in the field. Future researchers will get a clear insight about literature gap in the field of tourism industry.
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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 | 0.013 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.030 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".