286 Where Is On-farm Animal Welfare in the United States Headed? A Canadian Perspective
Bibliographic record
Abstract
Abstract Both the United States and Canada are major exporters of pork, with market forces and consumer demand playing a more important role than legislation in defining production standards. Canadian welfare standards can be seen as intermediate between those in America and Europe, with the province of Quebec leading the way in Canada’s production of “high welfare” pork. In many other respects- such as farm size, diets, genetics and management, pig farms in Canada and the United States are very similar. What can U.S. producers learn from Canada’s experience in implementation of new welfare standards? This talk discusses Canada’s 2014 implementation of the Code of Practice for the Care and Handling of Pigs. The Code included multiple new requirements, including the transition to group housing for gestating sows, use of analgesics at castration and tail docking, space allowances and the provision of enrichment. Code development is overseen by the National Farm Animal Care Council (NFACC) in cooperation with the Canadian Pork Council (CPC) and with participation of government, industry and public partners. In 2020, the Pig Code underwent a 5-year review, which resulted in eight major recommendations. Five of those recommendations will require amendments to the code and are yet to be approved. Each change illustrates a balance between economics and welfare in a highly competitive and changing industry. For example, the 2014 Code promoted adoption of group housing for sows by July 1, 2024. While integrated production systems committed to, and invested heavily in, implementation of group gestation, the cost of barn conversion and poor pork returns have been major deterrents on many farms. The CPC estimates that in 2021, 44% of Canada’s sow herd will be managed in groups. The Code review recognized that not all producers will be able to transition by 2024, and that forcing producers to convert on a strict timeline would result in a worsening of the animal’s welfare. The review recommended changing the date for implementation of group housing from 2024 to 2029. This more gradual transition will allow renovations to be part of a scheduled rebuild of an existing facility or new construction, with better long-term outcomes for producers and sow wellbeing.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.020 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".