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Record W2056262189 · doi:10.1177/1356766714542189

Understanding supply- and demand-side destination image relationships

2014· article· en· W2056262189 on OpenAlex
Shaojun Ji, Geoffrey Wall

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

VenueJournal Of Vacation Marketing · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMarketingPublicityPromotion (chess)AdvertisingGovernment (linguistics)Quality (philosophy)BusinessDestination imageChinaAffect (linguistics)TourismDestinationsGeographyPsychologyPolitical science

Abstract

fetched live from OpenAlex

Image promotion has been a primary focus of destination marketing. Marketers are eager to learn whether their projected images have been transmitted to potential consumers and are incorporated into their images of the destination. This research compares the images projected by Qingdao (China) government agencies and those perceived by current visitors. The projected and perceived images of Qingdao were investigated by analyzing publicity materials and a questionnaire survey of visitors, respectively. Their relationships were explored using both a qualitative evaluation and statistical tests. The results show that the two types of images incorporated certain common image themes. However, the emphasis of the projected images did not relate significantly to what visitors considered to affect the quality of their experience. Therefore, Qingdao’s projected image was only partially delivered to and embraced by current visitors.

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)0.016
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.342
Teacher spread0.225 · 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