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Record W7015780586

Understanding Chinese tourists' satisfaction with their travel experiences in Canada / by Kun Zhang.

2007· dissertation· en· W7015780586 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2007
Typedissertation
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismChinaConsumer satisfactionRelevance (law)Set (abstract data type)Order (exchange)Destinations
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study is to better understand Chinese tourists' satisfaction with their travel experiences in Canada. Primarily, tourism studies to date have addressed and examined the consumer or tourism satisfaction with services and destination performances. However, there is little research on Chinese tourists' satisfaction with their travel experiences to Canada, an issue of special relevance since China and Canada have begun to discuss Approved Destination Status (ADS) for Canada. This study seeks to examine existing Chinese tourists' expectations and satisfactions in order to meet their demands in the coming years. Participants in the study were Chinese tourists who have had recent travel experiences in Canada. Surveys were administered in Toronto during October to November 2005. Participants were asked to rate the importance of a set of attributes of tourism experience and then to assess performance on the same set of attributes.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.297
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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