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Insights on Wine Connoisseurs for the Wine Tourism Industry

2021· article· en· W3159136588 on OpenAlexaboutno aff
Vincent Fournier

Bibliographic record

VenueTourism Analysis · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsWineWineryVisitor patternTourismContext (archaeology)Consumption (sociology)MarketingAdvertisingWinemakingSociologyBusinessGeographySocial scienceArt

Abstract

fetched live from OpenAlex

This article suggests that studying wine culture may help to further understand wine tourism. The broader culture of wine consumption has an influence on the motivation and interest that people have for visiting a wine region or a winery. This study takes an anthropological approach to wine consumption culture and identifies specific topics of interest that connoisseurs find in wine and that may be relevant to wine tourism. The study is based on fieldwork and interviews with wine connoisseurs from Montreal (Canada). It identifies four main dimensions through which people engage with wine. The first factor concerns the formal discoveries offered by wine, the second, its social and cultural significance, the third, its producers and their values, and the fourth, the experimentation of theoretical knowledge in the context of wine regions. Each of these four dimensions offers a means for better understanding the visitor experience at wineries.

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)0.002
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 score0.116
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.007
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.249
Teacher spread0.224 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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