Integrative Governance for Ecological Public Health: An Analysis of ‘Food Policy for Canada’ (2015-2019)
Bibliographic record
Abstract
Normatively grounded in the ecological public health paradigm, this paper speaks to the role of public policy in addressing food and nutrition-related health challenges through a critical analysis of the 2019 Food Policy for Canada (FPC). We draw on primary data gathered through a SSHRC-funded Partnership Grant, Food: Locally Embedded, Globally Engaged (FLEdGE). Qualitative research methods include interviews with key stakeholders and policy makers, critical review of national food policy consultation documents, participant observation in government-, industry- and civil society-led conversations about the food policy, as well as an investigation of stakeholder responses to the FPC announcements of 2019. Our analysis focuses on how Canada’s new food policy: adopts an integrative, pan-Canadian approach; explicitly connects health and environmental dimensions of food; augments food security in a systematic way; addresses unique food security and health issues facing Indigenous Peoples; improves the health of food environments, such as those in Canada’s schools; and, meaningfully includes relevant stakeholders in food system governance. Against these expectations, we assert that the Food Policy for Canada does not yet provide an integrative, systems-based approach to addressing food and nutrition-related health issues consistent with the ecological public health approach, despite significant progress made. We conclude by proposing a research agenda for tracking Canada’s food policy implementation and development going forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".