Featuring Iconic Individuals on NTO Websites: A Catalyst for Cultural Tourism?
Bibliographic record
Abstract
This article explores the promotion potential of culturally iconic individuals through the examination of four countries' national tourism organization (NTO) websites. The four individuals—Australian Don Bradman, New Zealander Edmund Hillary, Canadian Terry Fox, and South African Nelson Mandela—are arguably the preeminent cultural representative figures in their countries. The stories of their physical practice and personal traits have been legitimized through social distinction to symbolize the character, ideals, and everyday way of life their country's cultures aspire to. The analysis of each NTO website reveals the frequency and prominence of references to culture generally, formal cultural descriptions, and the stories of these and other culturally representative individuals. The discussion focuses on potential reasons for the variance in formal descriptions and individual stories of culture across the websites. It is suggested one NTO website has a promotional strategy in which the culturally iconic individual transcends issues of site specificity and sustainability. This strategy, expanding from the recognized iconic individual to multiple stories of individual cultural representation, also provides a complex, nonhegemonic framing of a country's cultural way of life. The central contention of this article is that culturally iconic individuals can provide a promotional portal and catalyst for NTOs. Their symbolic stories uniquely differentiate, yet authentically frame, the integrated tourism experience of people, culture, and country.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".