New Gloss to Urban Heritage: The Discursive Repackaging of Scottish Cities as Wellness Retreats in Online Tourism Promotion Texts 2019-20
Bibliographic record
Abstract
The study, located at the intersection of Media, Tourism and Cultural Studies, is an analysis of the cultural identity of Scottish cities emerging from their on-line promotion as tourist destinations in the last pre-Covid-19 season 2019-20. It is argued that Scotland’s tangible and intangible urban heritage was consistently promoted as generating hedonistic, existential and spiritual experiences leading to an optimal state of individual well-being. The material under scrutiny involves official and independent tourism websites of six Scottish cities available on VisitScotland.com in 2019-20. Treated as cultural texts, they are analysed as evidence of the emergence of yet another commodified version of Scotland’s regional identity as a well-being paradise. The notion of place identity in the context of tourism is understood as a combination of selected physical attributes of a destination with a system of meanings and values attached to them by means of carefully planned discursive operations. Verbal discourse analysis is employed to demonstrate the prevalence of wellness discourse in the promotion of multifaceted urban heritage attractions. The term ‘palimpsest’ is proposed as a metaphoric description of the multi-layered place identities of the Scottish cities constructed in the texts under scrutiny. A concluding prediction is made that those identities constitute but a transient phase on the continuum of promotional efforts to adjust Scotland’s urban tourism offer to the changing consumer demand.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".