Discursive Institutionalism and Food Policy Research: The Case Study of Canada’s National Food Policy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
“Food” and “policy” are ambiguous concepts. In turn, the study of food policy has resulted in varying approaches by different disciplines. However, the power behind the discursive effects of these concepts in policymaking—how food policy is understood and shaped by different actors as well as how those ideas are shared in different settings—requires a rigorous yet flexible research approach. This paper will introduce the contours of discursive institutionalism and demonstrate methodological application using the case study example of Canada’s national food policy, Food Policy for Canada: Everyone at the Table! Selected examples of communicative and coordination efforts and the discursive power they carry in defining priorities and policy boundaries are used to demonstrate how discursive institutionalism is used for revealing the causal and material consequences of food policy discourses.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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 it