Quality Tourism in Thailand: Towards Sustainable Tourism or Further Wealth Concentration?
Bibliographic record
Abstract
In its long-term vision for tourism development (2017–2036), Thailand has chosen to focus on the development of quality tourism, which is supposed to enable sustainable tourism development and a more inclusive sharing of tourism-generated revenues. However, the use of the term “quality tourism” remains conceptually unclear, and the means by which quality tourism will enable a more inclusive sharing of wealth remain ambiguous. Taking the tourist island of Phuket as a case study, we question how quality tourism has materialized on the island and how it has affected the configuration of power between large international hotel chains and local hotel operators regarding tourism development. Guided by a critical political economy framework and based on a qualitative methodology involving triangulation of data collection among official documents, semi-structured interviews, and participant observation, we argue that quality tourism in Phuket, although justified as a form of sustainable tourism, is more akin to luxury tourism. This has led to greater concentration of wealth among large hotel chains and real estate groups who have taken advantage of quality tourism-related policies to boost their portfolios at the expense of local stakeholders.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".