521 Farm animal welfare: Maintaining public trust and social acceptability.
Bibliographic record
Abstract
Animal welfare is emerging as a key area of social concern in agriculture, such that we see increased public interest in how animals are housed and cared for on farms. Those working within agriculture sometimes believe that these concerns are mostly or entirely rooted in public ignorance of the practices, motivations and constraints faced by farmers, and thus believe that criticisms can be addressed through better public education. However, an ever-decreasing proportion of society works within the animal industries and it seems unlikely that efforts to ‘educate’ the public on these issues will often be successful. Moreover, the famers themselves are part of the rapid changes in societal views, and practices that were accepted by past generations may seem out of step for the next generation. To be sustainable in the long term the inclusion of societal input is needed for food animal production industries to retain their social license to operate. During this talk we highlight some of the contentious issues within the farm animal industries that are at risk of being out of step with societal values and possible solutions that may help pave the way forward in how we care and house farm animals.
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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 | 0.025 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".