MétaCan
Menu
Back to cohort
Record W2077294517 · doi:10.1002/jtr.401

The content of Third World tourism marketing: a 4A approach

2002· article· en· W2077294517 on OpenAlex
Charlotte M. Echtner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Tourism Research · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTourismDestinationsFrontierThird worldPromotion (chess)MarketingAdvertisingNatural (archaeology)Content analysisBusinessPolitical scienceGeographySociologySocial scienceEconomicsDevelopment economics

Abstract

fetched live from OpenAlex

Abstract Tourism to the Third World continues to grow and, correspondingly, the promotion of these regions is increasingly popular and important. Although some concerns have been voiced about the images contained in Third World tourism marketing, there has been no extensive examination of its content to date. Accordingly, in this study, the verbal and visual components of 115 brochures for 12 Third World countries are analysed. To facilitate a detailed content analysis of these brochures, a ‘4A’ approach is introduced, focusing on attractions (natural and man‐made), actors (hosts and tourists), actions and atmosphere . This comprehensive inventory reveals that Third World countries are clustered into three groups, namely Oriental, sea–sand and frontier. It is shown that by emphasising and stereotyping certain attractions, actors, actions and atmospheres, certain overarching tourism myths are created around Third World destinations. Copyright © 2002 John Wiley & Sons, Ltd.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.198
GPT teacher head0.411
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it