Canadian National Dairy Study: Describing Canadian dairy producer practices and perceptions surrounding cull cow management
Bibliographic record
Abstract
Farmer decisions surrounding culling have an important effect on the health and welfare of cull cows. The objectives of this study were to describe the self-reported shipment behaviors of Canadian dairy producers and understand farmer perspectives on the factors that were most influential in their decision to cull a cow. A nationwide survey was administered between March and April 2015 that included 192 questions covering producer background information, farm characteristics, biosecurity practices, disease prevalence, calf health, cow welfare, lameness, milking hygiene, reproduction, and Internet and social media use. The survey yielded a 12% response rate; a total of 1,076 respondents (78% of all survey respondents completed the culling section of the survey) were included in this study for analysis. Approximately 80, 51, and 38% of respondents reported shipping at least 1 cow to auction, direct to slaughter, and to another dairy farm in the past 12 mo, respectively. Ability of the cow to remain standing (93% of respondents) and drug withdrawal times (92% of respondents) were identified as the most important factors for consideration when culling cows. The time between culling decision and when the cow was actually transported was longer for lame cows than sick cows; almost 70% of respondents reported that cows culled for illness were typically shipped within 1 wk of culling decision, whereas only 51% of respondents indicated the same was true for lame cows. Last, Canadian dairy producers generally exhibited strong confidence that their culled cows would arrive at slaughter in the same condition as they left, but felt very unsure about knowing the location of their final destination. These results highlight several gaps between producer perceptions and the true situation, and can be used to develop tailored programs and inform policy and regulatory decisions aimed at improving cull cow decisions and cow welfare.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".