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Record W2020898567 · doi:10.3727/154427206776330535

Wine Tourism Research: The State of Play

2006· article· en· W2020898567 on OpenAlex
Richard Mitchell, C. Michael Hall

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTourism Review International · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsWineryVisitor patternTourismWineSophisticationMarketingProduct (mathematics)AdvertisingState (computer science)BusinessGeographySociologySocial science

Abstract

fetched live from OpenAlex

Research on wine tourism has expanded rapidly since the early 1990s with approximately two thirds of the literature coming from Australia and New Zealand, countries with not only substantial wine tourism but also a long record of wine marketing research. Of the remaining literature the dominant source countries for research are Canada and the US. Seven themes are identified from the literature and are discussed in turn: the wine tourism product and its development; wine tourism and regional development; the size of the winery visitation market; winery visitor segments; the behavior of the winery visitor; the nature of the visitor experience; and emerging area of research on the biosecurity risks posed by visitors. For each of the themes future research challenges and issues are identified. The review concludes by noting that although there is now a significant catalogue of research in the field, methods are still relatively crude and studies still tend to be regionally focused and quite generic in nature. There is therefore a need not only to improve the means by which results from different locations and populations can be compared but also to employ greater sophistication in the employment of qualitative and quantitative techniques in their examination.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.681
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.312
Teacher spread0.262 · 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