Culinary tourism as living history: staging, tourist performance and perceptions of authenticity in a Thai cooking school
Bibliographic record
Abstract
This study examined how a cooking school in Thailand acted as a site of living history in its staging and touristic experience of authenticity. The cooking school was one of the oldest, most visited and most comprehensively “staged” cooking schools in Bangkok. Research focused on understanding: (a) the nature of spatial and temporal staging of authenticity in the school, (b) tourists’ perceptions of authenticity and (c) parallels between the cooking school and living heritage sites. Findings showed that the cooking school was carefully designed to transport tourists from the heterogeneous tourist spaces of present-day Bangkok to the idealized, enclavic space of an imagined Thai culinary past. Tourists took on multiple roles, had rich sensory experiences, felt a sense of play and space–time transcendence, and revelled in close social relations with hosts and other tourists. These factors allowed them to experience multiple forms of both modernist and post-modernist authenticity. In its scenography, interpretative performance, narrative and rituals, the cooking school did indeed resemble a living history site. However, the school made no particular claim to expertise in Thai history, place or culinary culture, and tended more towards touristic entertainment, and less towards accurate historical and cultural visitor education.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".