Bibliographic record
Abstract
The COVID-19 pandemic has garnered public attention to Canada’s food security. Access to a safe, stable, and high quality food supply is often taken for granted by Canadians but it is one of the key roles that our agricultural industry serves and underlines why it is designated an essential service. Despite the federal government’s assurance that our nation’s food supply remains stable, concerns have been mounting from both consumers and the agricultural industry that disruptions in the food supply chain will cause food insecurity and severe economic distress. As a whole, Canada’s agri-food industry is well-positioned to adapt to the present crisis and continue supplying domestic and export markets. However, this does not mean that our food system is impermeable to disruption. In fact, challenges caused by COVID-19 have highlighted vulnerabilities in the food supply chain. Labour shortages, major shifts in consumer demand, and the slowdowns/closures at processing plants have already exacerbated food insecurity among Canadians and increased financial pressure on primary producers. As the foundation of the food supply chain, Canadian farmers are key to its stability. As many farms were experiencing severe economic hardship prior to the pandemic, the challenges of market uncertainty and increased production costs put these operations at greater financial risk. Policy action will be key to ensure the short and long-term viability of our primary industry and maintain the capacity to meet domestic and export market demands. Canada is still in the early stages of crisis management but government support of Canadian agriculture has been largely inadequate in alleviating the financial impact on farmers. The Canadian government must take immediate steps to alleviate the financial burden on primary producers, ensure export markets remain open and free from trade barriers, and commit to establishing a long-term agri-food strategy and action plan.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".