Moving Beyond the 3S's—Sun, Sea, and Sand: An Interpretation of the Tourism Development Strategy Framework for Abu Dhabi, U.A.E.
Bibliographic record
Abstract
This article unpacks the development of Abu Dhabi as a tourist destination, looking at its diversification strategy from the perspective of an oil-dependent economy attempting to move away from oil dependency. Based on a review of academic literature, government documents, and online sources, it fills a gap in understanding the growth trajectory Abu Dhabi has chosen in overcoming oil dependency. Abu Dhabi has gone beyond the 3S's to incorporate cultural tourism among its value propositions, as well as shopping and architecture; its strategy for sustainable tourism development embraces the economic, environmental, cultural, and social pillars of development. This article postulates a framework of tourism development for Abu Dhabi that shows movement beyond the 3S (or other multiple-S) model based on tourism attractions; the framework is important to inform both practice and policy with respect to tourism development in the U.A.E. and elsewhere in the world.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".