The Carrots and Sticks of Sustainable Farming in Canada
Bibliographic record
Abstract
Concerns about the way in which we grow, distribute and consume food around the world have grown in recent years. From the environmental impacts of farming practices (exacerbated by the industrialization of agriculture) and GHG emissions from agriculture, to the viability of farming communities and health concerns about concentrated livestock operations, the issues are numerous, often overlapping, and sometimes underpinned by different values and/or preoccupations. These concerns are intensified when set against the backdrop of expanding global population, with its growing need for food and increasing demand for diets high in both caloric and meat consumption, and climate change. Public policy in support of sustainable farming is essential to safeguard the ecosystems upon which farms are dependant, while providing sustainable rural livelihoods, promoting food security and contributing to a vibrant agricultural economy. This paper evaluates the extent to which Canada’s federal agricultural policy framework enables sustainable farming and agricultural food production. We find that, although there have been many ad-hoc initiatives within Canadian federal and provincial/ territorial governments relating to sustainability, Canada has not made any national policy commitments to pursuing sustainable farming. The government’s central agricultural policy framework fails to establish the enabling vision and incentive structure needed to influence a systemic change in the sector towards sustainable farming. The policy framework is primarily geared towards helping the sector become more competitive and gain and maintain market share, through innovation for instance. A shift in agricultural policy is required in order to safeguard the future of food security and rural livelihoods in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".