Harnessing food system equity from the ground up: shifting co-governance practices in the funding of food security responses during the pandemic crisis in Toronto, Canada
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
The COVID-19 pandemic was a disrupting force that magnified social inequities and service gaps in underserved urban communities. It was also a “window of opportunity” for the Black Lives Matter movement and Indigenous reconciliation synergies to spur calls to action for more open and inclusive dialog regarding community food security. Increasingly, community-based organizations (CBOs) that have not been traditionally food-focused are becoming more involved in food security responses. These factors have offered space to revisit antiquated and exclusionary practices within resource allocation and decision-making processes that reinforce systems of oppression within the food system. We explore the interconnection between CBOs, municipal actors, and funders in Toronto and draw upon the concept of co-governance to unpack their evolving relationships and influence on equity-focused change in policies and practices. Based on an analysis of interviews (n = 48), this paper articulates that a number of realized progressive, yet incremental, changes have been made, including changes to policies and internal practices and targeted support for Black and Indigenous communities. However, ultimately, a transfer of resources and influence is required in order to achieve the broader goal of harnessing food system equity.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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