Impacts of an African Swine Fever Outbreak on Ontario’s Pork Industry
Bibliographic record
Abstract
African swine fever (ASF), a highly contagious disease affecting domestic and wild pigs, has been spreading globally, with devastating impacts on hog markets. The European Union saw pork exports decrease by €556 million (9%) as a result of ASF outbreaks across four countries in 2014. Similarly, in 2018, when ASF was first reported in China, there was a 30% decrease in the Chinese pig inventory and in total pork production. ASF’s eventual spread to North America seems inevitable. Given Canada’s export-oriented pork industry, the economic costs and animal welfare impacts of an ASF outbreak in the Canadian hog sector could prove devastating as a result of potential border closures and large-scale animal depopulation. To estimate the impacts, we build a partial equilibrium, vertically integrated model of Ontario’s pork industry from the breeding herd through to end consumer. If an outbreak occurred in a central production region of Ontario, we estimate that Ontario’s pork industry would experience a welfare loss of C$860 million (28.1%). Conversely, if an outbreak occurred in Western Canada, the Ontario pork industry would benefit by C$198 million (6.5%). Not surprisingly, an outbreak will redistribute significant economic rents in the sector depending on where exactly the first outbreak occurs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".