Countryside capital, changing rural landscapes, and rural tourism implications in Mennonite Country.
Bibliographic record
Abstract
The purpose of this paper is to apply a framework of countryside capital to a culturally unique yet rapidly evolving rural landscape in Ontario, Canada. Countryside capital, a concept used to recast rural resources as capital assets of the rural tourism industry, reassesses the value of rural resources for rural tourism and sustainable rural development in the Waterloo region of Ontario. The region has a distinctive cultural heritage resource, the Old Order Mennonite culture and its unique rural landscapes. It also has a well-defined projected rural tourism product and image that have been altered over a short period of time from that of Mennonite Country to that of St. Jacobs Country. Furthermore, urban encroachment and the commodification of the rural landscape create conflict over the preservation of rural heritage. This study discusses these important issues in the context of countryside capital, as well as the implications for the future of tourism in the region and for rural sustainability in general. Perceptions of rural accommodation operators and their visitors, field observations, and an analysis of promotional literature provide an empirically based discussion. However, the case study acts as an illustration of the theoretical component that is the wider, in-depth application of countryside capital to a Canadian context. Keywords: rural tourism, countryside capital, cultural heritage, sustainability, bed and breakfast
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".