Bibliographic record
Abstract
Researchers concerned with the complex, interrelated, and multi-scalar relationships between culture and rural tourism development have explored both positive and negative dimensions in diverse contexts; however, more systematic attention to the concept of cultural sustainability is needed to design supportive rural tourism policies and processes. Wine and food tourism is one of the fastest growing rural tourism niches and intersects with critical cultural sustainability issues such as local food systems, food sovereignty and agricultural land use, therefore, it is particularly important to explore cultural sustainability in food and wine tourism contexts. Comparative case studies in two Canadian wine regions, British Columbia's South Okanagan Valley and Nova Scotia's Annapolis Valley, are used to gain a better understanding of the relationships between local food cultures, rural tourism development and sustainability in different provincial contexts with a particular emphasis on the role of related planning, policy and governance. Findings from semi-structured interviews and focus groups provide insights into how culturally sustainable food and wine tourism is conceptualized, recognized, developed, supported and promoted in each case. Processes and policies that support cultural sustainability are discussed and future research is proposed. This research is generously supported by a Rural Policy and Learning Commons (RPLC) Research & Exchanges Service Rural Policy Research Grant
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".