Agritourism as a Solution to Rural Revitalization: The Case Study of North Durham Region
Bibliographic record
Abstract
The agricultural industry has a prevalent, long-standing history as a successful cornerstone in Ontario. This historical prevalence stands true for the Regional Municipality of Durham’s three northern townships: Brock, Scugog, and Uxbridge. Agriculture and livestock are a driving force within the three township’s economies. However, throughout the last three decades, agricultural production in Ontario’s rural townships have been negatively impacted by vertical integration, globalization, and the intensification of land-based activities. This research examines the role of agritourism as a viable solution to revitalizing the agricultural sector in North Durham Region. This study utilized in-depth interviews with farm operators who have diversified their farming practices to understand these questions; the motivations of farmers to diversify their farms through agritourism, how agritourism assists farming businesses, and strategies farmers use to implement agritourism into their current farming practices. This research is imperative for farm operators in rural Ontario and policy makers to ensure farms are able to remain economically competitive against the pressures of urbanization and changing global markets.
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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 | 0.001 | 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 | 0.013 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".