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Record W1650861039 · doi:10.1080/19388160.2011.627029

Chinese Perceptions of Seven Long-Haul Holiday Destinations: Focusing on Activities, Knowledge, and Interest

2011· article· en· W1650861039 on OpenAlex
Dongkoo Yun, Marion Joppe

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of China Tourism Research · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of GuelphUniversity of Prince Edward Island
Fundersnot available
KeywordsDestinationsMainland ChinaTourismChinaMarketingAdvertisingBusinessProduct (mathematics)MainlandPerceptionCommissionGeographyPsychology

Abstract

fetched live from OpenAlex

This study analyzes Chinese views of seven selected long-haul holiday destinations using secondary data from the 2008 China survey of the Global Tourism Watch market research program commissioned by the Canadian Tourism Commission. Results indicate that Mainland Chinese travelers considered “culture” and “nature”the most important activity/experience factors when considering taking a long-haul holiday trip. Further, findings indicate that there are significant differences in Mainland Chinese travelers' perceptions toward the long-haul holiday destinations regarding the best travel activities/experiences, knowledge about holiday opportunities, and interest in visiting each of the destinations in the next two years. This study demonstrates the competitiveness of the seven destinations and suggests destination or product differentiation strategies to increase consumer awareness and attract more Mainland Chinese travelers.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.113
GPT teacher head0.436
Teacher spread0.323 · 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