Cultural Wine Tourists: Product Development Considerations for British Columbia's Resident Wine Tourism Market
Bibliographic record
Abstract
Emerging initiatives in British Columbia and elsewhere clearly suggest that by working with tourism stakeholders, the wine industry can not only contribute to the development of rural tourism, but it can also gain valuable direct marketing and value added sales advantages. For these benefits to be fully realized, more must be known about the character of travel markets interested in wine tourism. To provide insights into BC's domestic wine tourist markets, this research involves two overriding phases of investigation. Initially, it conducts an overview analysis of BC's domestic wine tourists. The second phase of the study involves describing a small but valuable and growing niche market of culturally oriented wine tourists. It then suggests several product development strategies suited to attracting and retaining such wine tourists. The strategies relate to incorporating a range of wine and non-wine related activities into the tourism experience, creating strong connections between local wines and regional cuisine, building cultural and heritage dimensions into wine tourism product packages, incorporating and promoting environmentally friendly resource management practices; and, protecting wine tourism landscapes. While the empirical part of this investigation is focused on BC wine tourists, the findings provide insights into strategies suited to other wine producing regions in Canada and elsewhere.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".