An advisory tool to improve management practices affecting calf and heifer welfare on dairy farms
Bibliographic record
Abstract
We developed an advisory tool addressing 10 critical areas of calf and heifer management, including calving management, care to newborn calves and painful procedures, colostrum management, cow-calf separation, calf feeding, weaning, calf housing, heifer feeding, heifer housing, and general monitoring. Targets and indicators for each critical area were validated by a panel of experts and maximum scores were assigned based on experts' opinions and reviews of scientific literature. The tool was tested on 28 Quebec dairy farms for feasibility and repeatability between 2 observers. Farmers were asked to test colostrum quality, measure blood IgG concentrations, and record health events. The on-farm evaluation included an interview on management practices and an evaluation of conditions in the barn. Scorings and recommendations were discussed with producers. The usefulness of our on-farm welfare tool was evaluated by the producers themselves during a final debriefing. We reached the main goals of a successful advisory tool of calf and heifer management to improve welfare on dairy farms. We respected the targeted time limit of a 3-h visit covering all aspects of our tool including data collection on management and environment, scoring, practical demonstration with producers, and debriefing. We had no problems collecting management- and environment-based data and had high repeatability of qualitative environment-based measures (kappa value>0.6). Our tool helped to detect problems and to discuss these problems with the producers; producers scored below 50% for some targets in calving management, care to newborn calves and painful procedures, colostrum management, and calf feeding. The targets were realistic so producers were not discouraged. All producers were convinced of the usefulness of our tool for identifying areas of calf and heifer management in need of improvement. They were also convinced of the usefulness of our tool as an advisory tool for technical advisors and veterinarians. Six months after the on-farm visit, recommended practices were implemented in many of these areas. Voluntary improvements in animal welfare can be facilitated by using appropriate tools to educate producers and help them change their attitudes toward calf management and animal welfare.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".