Global wine tourism: research, management and marketing
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.
Bibliographic record
Abstract
Introduction, J Carlsen and S Charters Section 1: The Wine Tourism Setting * Do Tourism and Wine Always Fit Together? A consideration of business motivations, R Fraser and A Alonso, Lincoln University, New Zealand * Land Use Policy and Wine Tourism Development, P Williams, Simon Fraser University, Canada, K Graham, Business Council of British Columbia and L Mathias, Canadian Cancer Society * Enhancing the Wine Tourism Experience: The Customer's Viewpoint, L Roberts, Victoria University, Melbourne and B Sparks, Griffith University, Australia Section 2: Wine Tourism and Regional Development * Wine Tourism and Sustainable Development, J Gammack, Griffith University, Australia * Emerging Wine Tourism Regions: Lesson for Development, B Sparks and J Malady, Griffith University, Australia * Determinants of Quality Experiences in an Emerging Wine Region, T Griffin and A Loersch, University of Technology Sydney, Australia Section 3: Wine Marketing and Wine Tourism * Influences on post-visit wine purchase (and non-purchase) by new Zealand winery visitors, R Mitchell, University of Otago, New Zealand * Electronic Marketing and Wine, J Murphy * Understanding the impact of wine tourism on post-tour purchasing behaviour, B O'Mahony, Victoria University, Australia, J Hall, L Lockshin, University of South Australia, L Jago, Victoria University, Australia and G Brown, University of South Australia Section 4: The Cellar Door * Wine tourists in South Africa: a demographic and psychographic study, D Tassiopoulos and N Haydam * Younger Wine Tourists: A study of generational differences in the cellar door experiences, S Charters and J Fountain, Edith Cowan University, Australia * The effects of survey timing upon visitor perceptions of cellar door quality, M O'Neill and S Charters Section 5: Wine Festivals and Events * Wine Festivals and tourism - a triangulated approach to festival satisfaction and quality, R Taylor, Curtin University, Australia * Wine festival: Analyses for attendees' motivational segmentation, and the event's promotional effects, J Yuan, Texas Tech University, USA, S C Jang, A C Liping and A M Morrison, Purdue University, USA and S Linton, Indiana Wine Grape Council, USA * A Strategic Approach to Wine Festival Development: The case of the Margaret River Wine Festival, J Carlsen and D Getz, University of Calgary, Canada Section 6: Wine Tours and Trails * Nautical wine tourism: A Strategic Plan to Create a Nautical Wine Trail in the Finger Lakes Wine Region of New York State, M Q Adams, University of Adelaide, Australia. * Wine Routes in Portugal, L Correia, Leiria Institute Polytechnic, Portugal and M Passos Ascencao, HAAGA University of Applied Sciences, Finland * Are we there yet? How to navigate the wine trails, D Hurburgh, Myriad Research Associates, Australia and D Friend Summary and Conclusions * The Future of Wine Tourism Research, Management and Marketing, S Charters and J Carlsen.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it