Calf management and welfare in the Canadian and US dairy industries: Where do we go from here?
Bibliographic record
Abstract
The objective of this narrative review was to compare the results of the 2015 Canadian National Dairy Study and the 2014 US National Animal Health Monitoring System (NAHMS) Dairy Studies, with a specific focus on calf management and welfare, and to interpret these findings within more recent calf health research to describe where we need to go next in the North American dairy industry. Situating results of periodic national studies within the context of past and recent research provides an opportunity to gauge adoption of recommendations and best practices and to help identify persistent and new challenges that the industry is wrestling with to help guide research needs. Through this review of the 2 national studies, we identified several strengths of the Canadian and US dairy industries. In each area of calf health management, improvements relative to previous NAHMS studies and the published literature have been found in the level of mortality, amount of colostrum fed, housing, and the number of producers using pain control for disbudding and dehorning. There were, however, some areas that present clear opportunities for improvement. Specifically, although mortality levels have improved, a large number of calves die at birth, within the first 48 h of life, and during the preweaning period. To improve the health of calves in early life, producers could look at feeding high-quality colostrum at 10% of body weight in the first feeding, as well as feeding a larger amount of milk during the preweaning period. The barriers to making these management changes and improving overall calf health need to be identified in future studies. The majority of preweaning calves in Canada and the United States are housed in individual housing. This represents a clear opportunity for improvement because recent research has identified the positive aspects of group housing. Finally, with respect to pain control, improvements are needed (particularly in the United States) to ensure that pain management is provided when disbudding and dehorning calves. Although the science is clear on pain management, discussions with producers are needed to identify reasons for the lack of uptake.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".