Describing the decision-making process of Ontario dairy farmers when managing down dairy cattle: A qualitative focus group study
Bibliographic record
Abstract
The objective of this study was to investigate Ontario dairy farmers' attitudes and perceptions toward down dairy cows, and the barriers and motivators influencing the use of best management practices. Four focus groups were conducted in southwestern Ontario in 2024, with a total of 21 dairy producers participating. Producers were asked about current practices, thoughts on best management practices, challenges to adopting best practices, and facilities and equipment for down cow care. The focus groups were audio recorded, transcribed, and analyzed using applied thematic analysis. Five themes were identified from the data: adaptive and flexible management strategies; farm resources and facilities; veterinary relationships and communication; producer experience and emotional impact; and animal-centered decision making. Producers emphasized a balance between proactive, long-term strategies, such as prevention, record-keeping, and research-driven improvements, and the need for flexible, real-time decision making to address the unpredictable nature of down cows. Facility design, labor availability, financial constraints, and veterinary collaboration played important roles in the care they provided to down cows. Further, producers highlighted the emotional burden of making euthanasia decisions and discussed the balance of animal welfare and economic sustainability. Producers also expressed a need for more research, better diagnostic tools, and practical on-farm solutions to improve down cow management. Addressing these challenges requires coordinated efforts that integrate practical tools, infrastructure improvements, producer education, and veterinary support systems. The interplay of these factors underscores the need for a holistic approach to support producers in navigating the multifaceted challenges they face in their daily work. This study contributes to understanding the multidimensional factors influencing dairy producers' management practices in caring for down dairy cows.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".