Moving beyond awareness to action and food system transformation: prioritizing labor in food systems governance work
Bibliographic record
Abstract
The COVID-19 pandemic laid bare many of societies’ existing social and economic inequalities, one of which is illustrated in the challenges facing food and farm workers across the food chain. Despite this upsurge in public recognition, the circumstances facing food and farm workers remain unchanged, and this lack of action is reflected within the work of food systems-focused civil society organizations (CSO) in Canada. Several authors have noted the lack of recognition of labor issues within food systems work. This paper further explores the nature of this disengagement, particularly in food systems governance work, and identifies barriers to more meaningful engagement and possible avenues to overcome these challenges. Findings draw from a set of 57 interviews conducted from 2020 to 2023 with a range of food system CSO representatives across Canada, examining their understanding of, and engagement in, food systems governance work and their involvement in labor issues (or lack thereof). The paper concludes that though there exists widespread awareness of the challenges facing food and farm workers, and a desire to engage in a more sustained fashion, many food system CSOs have not yet found the tools or pathways to do so on an organizational level. Several discursive openings are identified that offer an opportunity to leverage the heightened awareness of food and farm workers during the pandemic into concrete collective action.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".