COVID-19, a changing food-security landscape, and food movements: Findings from a literature scan in Canada
Bibliographic record
Abstract
This research brief presents results from a scan of peer-reviewed and grey literature published from March 2020 to the end of August 2021 looking at the impacts of COVID-19 on food security in Canada. The purpose of this literature scan is to look at how the national food-security landscape has shifted due to the pandemic and to analyze what these changes mean for civil society–led food movements working on the ground to enhance food systems sustainability and equity. This brief presents key findings from the literature scan focusing on food-security policy, programming, and funding; food security for individuals, households, and vulnerable populations; and food systems. We then draw on our collective experiences as food scholars and activists to discuss the implications of these findings for food movement organizing. Here, we focus on networks, policy advocacy, and local food systems as key considerations for food movements in a changing food-security landscape.
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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.057 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".