Food Tours in the Context of Multiculturalism Of Tourism Destinations: The City Of Dubai As An Example
Bibliographic record
Abstract
Food tourism is closely related to cultural and heritage tourism. Food tourists are experiencing the culture of a destination through tasting its national dishes and traditional cuisines. Most major countries around the world have their special food which is considered as a characteristic of a particular destination. Food is a very important part of the tourism product and it is involved into the marketing plans in many countries. Therefore, food is considered one of the factors that tourist consider when they choose a tourism destination. Food tasted by tourists is playing a major role in impressing them and might make them come back again and again to the same destination. Specialized food tours have emerged in concert with the growing interest in, and demand for, authentic cultural tourism experiences. The study aims to represent the importance of food tours in expressing the identity and culture of countries and how food tourism is an important element of the intangible heritage. Some countries have their own particular cuisines or national dishes while others have no special cuisine due to the multicultural nature of these countries such as Canada, New Zealand, Australia and United Arab Emirates in the Middle East. The study sheds the light on the importance of food tours within the intangible heritage frame. It discusses the importance of food and gastronomy in multicultural countries from the theoretical point of view through the literature review and analysis. The importance of food tourism in the city of Dubai as a cosmopolitan city and reasons behind the recent growing and popularity of food tours in the city are also represented in this study.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".