Farm Resilience in Southeastern Ontario: A Comparative Study of Alternative and Conventional Farms
Bibliographic record
Abstract
Southeastern Ontario presents a unique agricultural landscape in which both alternative and conventional farms operate. Each category of farm experiences a wide range of environmental and socio-economic shocks and stresses that threaten each farm’s longevity, raising policy questions about what constitutes ‘sustainable agriculture’. Yet in Ontario there presently exists no unifying policy framework for building agricultural sustainability and current rubrics emphasize continuity over transformation. In response, this thesis mobilizes an analytical framework based on resilience thinking to create a holistic method for assessing farm sustainability. Implementing this approach in the study area of Inverary, South Frontenac, semi-structured interviews were conducted with a range of both conventional and alternative farmers. These enable the thesis to identify primary shocks and stresses experienced at the farm level and account for the ways that their operations are structured to mitigate risks and achieve valued outcomes. Additional interviews with OMAFRA employees and other key figures from provincial agricultural organizations and economic development offices supplemented the direct accounts of farmers. This research found that alternative and conventional farmers are facing different sets of issues and are therefore prioritizing different responses to those threats. This research also found a strong discrepancy between the notions of sustainability as portrayed by OMAFRA and the notions of sustainability portrayed by the actions of farmers around Inverary. Key findings are summarized via policy recommendations in efforts to create a forward-looking vision of agricultural sustainability in the province.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".