Bibliographic record
Abstract
Growth trends in life-long learning, and rural tourism indicate potential for the rural educational tourism sector; however; there is very little empirical research on how this niche tourism, which may include activities such as, agricultural school excursions/exchange programmes, “farm-to-table” culinary courses, artisan craft programs, etc., might build local capacity, support sustainable rural economies, and mobilize place-based ways of learning that are required for global sustainability. This research project, which is at the conceptual/exploratory stage, aims to explore the economic, social and environmental impacts of rural educational tourism. There is no existing research that brings together rural development and place-based educational tourism in a Canadian context. Sub-questions with particular relevance to rural development policy and planning include: How was rural educational tourism integrated within a greater economic and learning development strategy? What new roles and competencies did stakeholders require and how were they developed? What changes from traditional forms of policy development were required? How were issues of sustainability, environmental impact, and conservation addressed? How did the quality and quantity of interconnections change? Since educational tourism has received very little research attention, comparative case studies with mixed methods are a suitable approach. I hope to include educational tourism activities in rural Aboriginal communities, pending consultation, and with an understanding of Aboriginal research as being research by and with Aboriginal Peoples. My approach emphasizes and values the existing strengths, assets and knowledge systems of rural communities.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".