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Record W2087944194 · doi:10.1177/1356766711409185

Wine tourism: Winery visitation in the wine appellations of Ontario

2011· article· en· W2087944194 on OpenAlex
Hillary Dawson, Mark Robert Holmes, Hersch Jacobs, Richard Wade

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 Vacation Marketing · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsToronto Metropolitan UniversityWine Council of Ontario
Fundersnot available
KeywordsWineryTourismGeographyAdvertisingWineInfluencer marketingDestinationsWine tastingPeninsulaAccommodationConsumption (sociology)MarketingBusinessSociologyArchaeologyPsychology

Abstract

fetched live from OpenAlex

This study explores various factors that encourage travel to wineries in the Ontario viticultural regions of the Niagara Peninsula, Prince Edward County, Pelee Island and Lake Erie North Shore. A convenience sample of 1309 visitors at 19 wineries revealed that the winery experience was not the primary purpose of the trip for a majority of the visitors but was a major influencer in their decision to travel to the regions. Planning typically began within three weeks of departure when friends, family and local websites provided the principal sources of information. Differences were observed among the four regions in demographic profile, motivations, influencers and consumption behavior. Proprietary tasting events and comprehensive wine tour packages including fine dining and overnight accommodation were suggested products that would attract more visitors whose on-site purchases were critical to the success of many operations.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.225
Teacher spread0.192 · 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