Tourist, Local, and Broker Perceptions of Abu Dhabi and Dubai, United Arab Emirates: Tourist Gazes, Ultra-Artifacts, and Hyperreality
Bibliographic record
Abstract
The globalization of tourism has dramatically influenced the construction of destinations, as well as the demand for novel experiences in such places as the Emirate of Abu Dhabi and Dubai in the United Arab Emirates. As tourism providers work to immerse visitors in innovative tourism sites characterized by wondrous architecture with extreme technological enhancements, it becomes critical to develop a new and comprehensive understanding of experiential travel. This study employs a mixed-methods research design to develop insights on concepts of tourist gazes, ultra-artifacts, and hyperreality by delving into processes and interactions between brokers, locals, and tourists within natural and built environments. Tourism in Abu Dhabi and Dubai entails a dynamic interaction between ultra-artifactual components and travelers in the pursuit of contrast. Tourism gazes facilitate immersive experiences of hyper-real tourism spaces. This research contributes to Urry’s sociological studies on tourist gazes by introducing a new set of ‘hyper-gazes’ that capture individuals’ stimulating encounters that redefine reality. Findings underscore the importance of perceptions in understanding the design of hyperreal productions and tourism development in the future.
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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 | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".