Tourism and Poverty Alleviation: An Integrative Research Framework
Bibliographic record
Abstract
The past decade has seen an upsurge of interest from the governments and development organisations in a tourism-based approach to poverty alleviation. More specifically, poverty alleviation has been established as a major priority within the United Nations World Tourism Organisation (UNWTO) itself, as is evidenced by the launching of the concept of ST-EP (Sustainable Tourism as an effective tool for Eliminating Poverty). In contrast, the implications of tourism for poverty alleviation have been largely neglected by the tourism academic community. Relevant research to date is fragmented, limited in scope, and lacks a consistent methodological development. To address these deficiencies, this paper presents an integrative research framework, which synthesises multiple perspectives and can be used as an overarching guideline to stimulate and guide other future enquiries on tourism and poverty alleviation. Towards this end, a number of research needs and opportunities have also been identified and suggested along with the presentation of the framework.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| 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".