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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 OpenAlexaff
Mao-Ying Wu, Geoffrey Wall, Yixuan Tong

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.021
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.468
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations17
Published2019
Admission routes1
Has abstractyes

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