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Record W2059152237 · doi:10.1300/j073v21n01_03

Relationship Between Wine Involvement and Wine-Related Travel

2007· article· en· W2059152237 on OpenAlex
Graham Brown, Mark E. Havitz, Donald Getz

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Travel & Tourism Marketing · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsUniversity of CalgaryUniversity of Waterloo
Fundersnot available
KeywordsWineTourismAdvertisingBusinessMarketingGeographyFood scienceChemistry

Abstract

fetched live from OpenAlex

This research was conducted to examine the nuances of special interest wine markets in terms of day-to-day consumption and travel-related patterns. A demographically diverse set of respondents (n = 161) were recruited from wine clubs and wine events at a western Canadian city. Based on previous involvement research a reliable and valid fifteen-item, three-faceted Wine Involvement Scale (WIS) was developed. Respondents were placed into one of four market segments based on their responses to the WIS. Although between market demographic differences were minimal, consumptive behaviours related to wine and wine tourism were consistent and profound (p < .05). Discussion focuses on marketing implications for special interest wine tourists and on conceptual challenges related to high-end market research. [ABSTRACT FROM AUTHOR]

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.247
Teacher spread0.218 · 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