Canadian Agri-Food Export Opportunities in a Covid-19 World
Bibliographic record
Abstract
As with the wider Canadian economy, the Covid-19 pandemic has represented an unprecedented shock to agri-food supply chains. Given the importance of Canadian agri-food exports, it is vital that supply chains rebound from the shock and disruptions are minimal. If this occurs, they should be able to respond to opportunities created by the supply chains of international competitors having to deal with Covid-19 in export markets. The demand for food is expected to increase in step with the forecast rise in global population to over 9 billion by 2050. In the next decade alone, total food use for cereals is forecast to grow by 1.2 per cent annually for cereals, 1.7 per cent for animal products and 1.9 per cent for pulses/roots and tubers. Agricultural production to be used as food, feed and in industrial applications will increase by 15 per cent in the next decade (OECD/FAO 2019). Canadian agri-food supply chains are well positioned to meet these future needs so long as they can maintain their resiliency. While the Covid-19 pandemic has not yet run its full course, it is already clear that Canadian agri-food supply chains, both those involved in provisioning the domestic market and those serving export destinations, have proved to be resilient in the face of the pandemic’s shocks and are rapidly returning to the high levels of efficiency they possessed prior to Covid-19. In the domestic market, while there were short run disruptions for some products, there were always sufficient substitutes on the shelves such that there was no threat to food security. As incomes fell, there have been increased calls on foodbanks but these are problems with the wherewithal to purchase, not food availability. Domestic supply chains proved themselves to be robust in dealing with major shocks including the shift to food consumed at home. The international supply chains for agri-food products also proved very resilient and are now well positioned to take advantage of opportunities. Some other countries’ supply chains have not proved as resilient or have suffered from government policy interventions. A number of Canada’s major competitors have imposed export bans, creating market opportunities that Canada could fill. Other competitors have been slower to deal with illness in their workforces. In some importing markets, their domestic supply chains are struggling, creating opportunities for imports from Canada. Due to projected global population growth, the increasing international market for major Canadian agricultural products such as wheat, beef and pork, and canola, are lucrative targets for Canada’s economic recovery and growth. Canada’s future success, however, depends on its agri-food supply chains not being encumbered by reactive regulations that reduce their efficiency, and by supportive policies that ensure producers in the supply chain weather the short-term pain from the Covid-19 crisis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".