Revisiting the effects of the COVID‐19 pandemic on Canada's agricultural trade: The surprising case of an agricultural export boom
Bibliographic record
Abstract
Abstract In contrast to April 2020 forecasts of the effects of the pandemic on Canada's agricultural trade, we find 1 year later that the recession was deeper, that total trade fell by less than was widely expected, and agricultural trade did not fall but actually increased. This was a general pattern across countries, but Canada's agricultural trade increased by at least 11%, more than the world aggregate and that of the U.S. This was mostly due to the success of crop exports, specifically in oilseeds, lentils, and cereals. Although some of the increase was due to rising commodity prices, for the most part trade volumes also increased substantially. Not only was Canada's export boom not expected but it was also not closely related to the pandemic. It was due to commodity‐specific circumstances, such as China's rebuilding of its depleted hog herd, a short crop of lentils in India, and demand shifts to Canadian wheat, durum and barley. Increased Asian demand helped this export growth, but accounted for less than a third of it.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".