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Record W2921470470 · doi:10.1080/19388160.2018.1516584

Research on China’s Inbound Tourism: A Comparative Review

2019· review· en· W2921470470 on OpenAlex
Mao-Ying Wu, Geoffrey Wall, Yixuan Tong

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 China Tourism Research · 2019
Typereview
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChinaTourismContext (archaeology)Government (linguistics)Regional scienceDomestic tourismTourism geographyMacroMarketingEconomic geographyBusinessPolitical scienceGeography

Abstract

fetched live from OpenAlex

This study explores the current status of research on inbound tourism to China, which ranks third globally among tourist receiving countries. The importance of inbound tourism as an indicator of national tourism competitiveness and the current slow growth of inbound tourism in China make this review timely. A bibliometric approach is used. Articles published with CSSCI (Chinese Social Science Indexed) journals and international studies published in English-language journals were identified. Analysis of over 700 domestic articles about inbound tourism indicates that the studies concentrate on macro issues, in particular the spatial and temporal distribution of the inbound tourists and their economic impacts. Few studies on Chinese inbound tourism have been published in English language journals. The most popular theme is tourists’ behaviors. A comparison between publications in two languages is made and implications are offered in the context of the Chinese government’s policies on inbound tourism and the current status of research.

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)0.086
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0860.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0070.008
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0090.002
Research integrity0.0010.021
Insufficient payload (model declined to judge)0.0040.005

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 head0.468
GPT teacher head0.594
Teacher spread0.126 · 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