Appreciative Inquiry and Rural Tourism: A Case Study from Canada
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
Abstract Many Canadian, resource-based communities are facing an economic crisis and often turn to tourism for economic diversification and some recent trends in the growth of tourism employment in Canada's rural areas suggest that such choices are well founded. Despite positive growth indicators, rural tourism is criticized for several reasons, including issues with employment, ownership and lack of understanding of the industry. Although much has been written on the development of community-based tourism and its potential to address such concerns, much of the discussion remains at theoretical levels, with few examinations of practical frameworks for rural communities in crisis, such as the current experience in North-western Ontario, Canada. Enquiries into tourism's contribution to rural community economic development identified two gaps concerning how rural tourism can be a viable industry in resource-dependent communities and how to embed the industry within a community seeking alternatives from a deficit/crisis context. Interviews with a tourism operator in rural Manitoba, Canada seemed to provide an answer to both of these questions, through the application of Appreciative Inquiry (AI) to rural tourism development. Such an examination indicates that although such an approach does not solve the issues, it does provide a new lens through which to understand the potential for tourism in rural communities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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