A Unique Rurality: Exploring the Role of the Horse Farm in the Post-Productivist Rural Landscape
Bibliographic record
Abstract
This thesis explores the role of the horse farm in the post-productivist rural landscape of Ontario, Canada. As agricultural landscapes in developed nations around the world evolve to an increasingly consumptive focus as opposed to a productivist landscape, there is an increased demand for recreational and lifestyle land uses in rural regions. Horse farms and equestrian activities are one of these consumptive land uses that also have connections to the agricultural community. A comprehensive literature review of multifunctional landscape, post-productivism, and current trends in the equine industry in Ontario is presented in this thesis. In addition to the literature review, a survey of 952 members of the Ontario Equestrian Federation was conducted on the general themes of landscape multifunctionality with three broad categories of production, ecological, and community functions as the principle areas of investigation. The survey elicited a 61% response rate. The results provide a description of the demographics of the sport and recreation sector of the equestrian industry in Ontario as being primarily female, active in their communities, concerned and interested in environmental stewardship, and strongly attached to their horses and their properties in rural Ontario. The survey results suggest a unique sector of the rural landscape has been overlooked in government policies and programs and provides recommendations for future research and suggested policy initiatives. Results of this survey also suggest that the trend towards a pluralistic and consumptive rural landscape is occurring in Ontario and that horse farms are an important part of this trend.
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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 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".