Governance recommendations from forty years of national food strategy development in Canada and beyond
Bibliographic record
Abstract
This paper contributes to Canada’s current national food policy discussion by introducing lessons gleaned from the development of two earlier Canadian government food policy efforts, A Food Strategy for Canada (1977) and Canada’s Action Plan for Food Security (1998), as well as lessons drawn from national food strategy development in seven other countries. By examining the strengths and weaknesses of these previous policy-making processes, we show how today’s food policy conversation builds on the legacy of 1998's Action Plan. We then offer food policy governance recommendations designed to avoid the mistakes of the previous efforts. This paper explores international precedents for governance mechanisms designed to be inclusive of key food systems’ stakeholders, and to meaningfully include multiple levels of government in food governance. Drawing on both our domestic and international research, we conclude by recommending the establishment of a multi-sectoral and inter-governmental National Food Policy Council. We show how such a Council, operating in close cooperation with other key mechanisms, could help govern the pan-Canadian food strategy we advocate.
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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 | 0.031 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".