How benchmarking promotes farmer and veterinarian cooperation to improve calf welfare
Bibliographic record
Abstract
Little is known about the combination of factors that motivate changes in calf management on dairy farms. Providing information to farmers may help promote change, but it is unclear how this approach affects and is affected by the farmer's relationship with the advisors such as the herd veterinarian. The goal of this study was to understand how benchmarking measures related to calf immune development and growth affected farmer and veterinarian cooperation and influenced the farmer's view of the veterinarian as an advisor for calf management. Veterinarians provided their clients (n = 18 dairy farms in the lower Fraser Valley of British Columbia) with 2 benchmark reports providing information on transfer of passive immunity and calf growth. Farmers were interviewed before and after receiving these reports to understand how they perceived their veterinarian as a calf advisor. Qualitative analysis identified 2 major themes indicating that benchmarking (1) improved farmer perception of their veterinarian's capacities to advise on calves and (2) strengthened the social influence of the veterinarian. We conclude that benchmarking can help promote stronger relationships between farmers and veterinarians.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".