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Record W2623056382 · doi:10.1080/09571264.2017.1336081

Integrated rural wine tourism: a case study approach

2017· article· en· W2623056382 on OpenAlex
Mark Robert Holmes

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.

Bibliographic record

VenueJournal of Wine Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTourismExperiential learningMarketingWineRural tourismPeninsulaWork (physics)BusinessRural areaExplanatory powerOrder (exchange)Rural developmentGeographyTourism geographySociologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Using the Niagara Peninsula Appellation as the case study, qualitative research was employed through the use of interviews conducted with wineries and industry associations, in an attempt to answer two specific questions: (1) how does the wine industry and wine tourism aid in the development of Niagara’s rural area using the integrated rural tourism (IRT) concept, and (2) how can IRT aid in rural development through direct, experiential, conservation, development, and synergistic benefits. It is apparent that the seven components of IRT provide a reasonable framework to analyse the ability of IRT to realize benefits, although that the addition of marketing and future needs/desires as components improve its explanatory power. Using the modified IRT framework, this research found that wine tourism has derived direct, experiential, conservation, and synergistic benefits, with work still to be undertaken in order to improve upon tourism’s positive impacts in Niagara and peripherally rural areas more generally in the areas of community engagement and improved industry synergy.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.002
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 head0.142
GPT teacher head0.381
Teacher spread0.239 · 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