Food sovereignty in Canada: Emerging actors and competing ideas in national agri-food policymaking
Bibliographic record
Abstract
Food sovereignty has recently gained increasing prominence as an alternative framework for agri-food policymaking. In Canada, food sovereignty actors are engaging with domestic agrifood policy issues; yet their activities targeting national policymaking have not been subject to systematic study. My research seeks to fill this gap by explaining food sovereignty actors' engagement in, and efforts to influence, federal policymaking processes. Using a case study research design that examines the period between 2009 and 2015, I demonstrate how Canadian food sovereignty actors have interacted with the federal policymaking process by initiating public debate over agri-food policy and forming strategic alliances with agri-food policymaking stakeholders. Furthermore, I show how food sovereignty actors promote ideas about autonomy and public engagement in federal policymaking, and explain the significance of these ideas compared to existing theories of agri-food policymaking in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".