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Record W2090511514 · doi:10.1108/09596110810866118

Key challenges in wine and culinary tourism with practical recommendations

2008· article· en· W2090511514 on OpenAlex
Jeffrey W. Stewart, Linda Bramble, Donald Ziraldo

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

VenueInternational Journal of Contemporary Hospitality Management · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsBrock UniversityNiagara College
Fundersnot available
KeywordsWineTourismKey (lock)MarketingBusinessHospitalityHospitality industryAdvertisingPolitical scienceFood scienceComputer science

Abstract

fetched live from OpenAlex

Abstract Purpose – The purpose of this paper is to present recommendations for future growth and continued success of wine and culinary tourism in the Niagara region. Design/methodology/approach – Through industry interviews with practitioners, researchers and stakeholders the recommendations of this paper were formed. Secondary research examined the issues and advances made in other area of the globe specific to wine and culinary tourism. The research is intended to cover the issues associated with advancing an industry sub‐sector that is still growing but will reach maturity in not‐so‐distant future. Findings – In Niagara's wine and culinary tourism sector, there is a renewed call for industry specific research. Furthermore, linkages across the border are recommended to increase tourism revenue both in the USA and Canada. There is need to create more domestic awareness of the changes. Additionally, in order to attract one‐time visitors back to the region, it is important to enhance service through increased service training. There also exists a need for cooperation and coordination within the industry at all levels. The final recommendation is to advocate for signage and specific information to varied segments of the wine and culinary target market sub‐sets to deal with the differences in consumer motivations and preferences. Originality/value – The relevant conclusions and recommendations listed will assist practitioners to continue the forward momentum of wine and culinary sectors in Niagara and around the world.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.072
GPT teacher head0.290
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