Conflicting and Silent Voices: How Sustainable Agricultural Narratives Replace and Shape Policies in Ontario, Canada
Bibliographic record
Abstract
Ontario's agriculture and agri-food sector currently accounts for over one-quarter of all farms in Canada.However, the province does not have any official definition for sustainable agriculture, making it difficult if not impossible to address cumulative environmental challenges.Rather, Ontario has a piecemeal basket of agricultural policies, which encourage ineffective and unsustainable business-as-usual policies.As a result, multiple contrasting and competing visions are pushed by various stakeholders, most of whom favour larger conventional operations as opposed to smaller, more ecologically sound ones.Using Thompson et al. (2007)'s four types of sustainable agricultural narratives (Growth, Production-Innovation, Agroecology, and Participation), this paper will analyze what specific discourses take privilege over others, and how these discourses shape or maintain policies to their favour.In order to encourage an agricultural sector that is sustainable and equitable in the long run, Ontario must adopt a cohesive set of cumulative agricultural policies for its various eco-regions.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.053 | 0.017 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".