Practices for the disbudding and dehorning of dairy calves by veterinarians and dairy producers in Ontario, Canada
Bibliographic record
Abstract
Disbudding and dehorning dairy calves is very common, despite the introduction of polled genetics to most dairy breeds. Appropriate pain-control practices for these procedures affect both calf welfare and public perception of the dairy industry. Previously published work has shown that North American dairy producers have not widely adopted use of these medications for disbudding or dehorning. However, since the last published work examining these practices in Canada, changes regarding awareness, availability, and future requirements for pain control have occurred in the industry. With this in mind, online and telephone surveys of both veterinarians (n=238) and dairy producers (n=603) in Ontario, Canada, were conducted in the fall of 2014 with a goal of describing current disbudding and dehorning practices and examining factors associated with the adoption of pain control use. Approximately three-quarters of dairy producers reported performing disbudding or dehorning themselves, whereas the remainder used a veterinarian or technician. Almost all (97%) of the veterinarians surveyed reported using local anesthetic, 62% used sedation, and 48% used a nonsteroidal anti-inflammatory drug. Producer use of local anesthetic was 62%, 38% used sedation and 24% used a nonsteroidal anti-inflammatory drug. Seventy-eight percent of veterinarian disbudding or dehorning was done before 8wk of age, whereas 64% of dairy producers performed this procedure before 8wk of age. Seventy-two percent of veterinarians and 63% of producers reported changing their disbudding or dehorning practices over the past 10 yr; of producers that changed their practices, 73% cited their herd veterinarian as influential. The use of pain control described in these surveys is higher than previously reported in Ontario. Identification of factors associated with best practices, or the lack of adoption of these practices, may help veterinarians target appropriate educational opportunities for their dairy clients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".