Consultation of pig farmers on the inclusion of some welfare outcome assessments within UK farm assurance
Bibliographic record
Abstract
Fifty-six pig farmers who attended a series of health seminars completed a questionnaire to assess their attitude to the inclusion of some welfare outcome assessments within farm assurance. In answer to open questions, farmers were most commonly proud of the productivity (27.5 per cent) and welfare (23.5 per cent) of the pigs on their farm, and the welfare of pigs in the UK industry as a whole (26.1 per cent). The most common thing that farmers wanted to tell consumers about was the welfare of the pigs (55.8 per cent), followed by their stockmanship qualities, the quality of their pig meat and the safety of their pig meat (all 13.5 per cent). In answer to closed questions, 66 per cent of farmers stated they would be either quite willing or very willing to perform welfare self-assessments as part of farm assurance, and 66 per cent would be quite or very willing to be anonymously benchmarked on the welfare of their pigs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".