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Record W2529804149 · doi:10.3968/8674

The Details Exploration of Intangible Cultural Heritage From the Perspective of Cultural Tourism Industry: A Case Study of Hohhot City in China

2016· article· en· W2529804149 on OpenAlexvenueno aff
Yafeng Wang, Zekun Zhou

Bibliographic record

VenueCanadian social science · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsIntangible cultural heritageCultural heritage managementTourismCultural heritageIndustrial heritageChinaValue (mathematics)Cultural tourismTourism geographyPerspective (graphical)BusinessEnvironmental ethicsMarketingPolitical scienceArtVisual artsLaw

Abstract

fetched live from OpenAlex

the intangible cultural heritage is an important part of the cultural tourism industry marketing.As the cultural element ,the intangible cultural heritage can impel the main cultural tourism industry become more diversified and more extensively involved of public.Intangible cultural heritage can enhance the experience of tourists in culture . The intangible cultural heritage of Hohhot has an important value ,. keeping up with the times and has gone through long history, it is synchronic,all this can increase the value of tourism destination by explorating the innovation of intangible cultural heritage.With the help of real drama culture, the local brand value of intangible cultural heritage can be created. And it can realize the endorsement value of the people speaker.  This article explores the intangible cultural heritage from the perspective of cultural tourism in order to promote the tourism development in Hohhot.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.197
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.121
GPT teacher head0.289
Teacher spread0.168 · 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 designObservational
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

Citations7
Published2016
Admission routes1
Has abstractyes

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