How can better calf care be realized on dairy farms? A qualitative interview study of veterinarians and farmers
Bibliographic record
Abstract
Improving health and welfare outcomes for replacement and surplus dairy calves is important for the sustainability of the dairy industry. Dairy farmers and veterinarians hold expertise in calf management and have valuable perspectives on how to practically motivate improvements. The objective of this study was to determine strategies that could improve the care calves receive on dairy farms from the perspective of dairy farmers and their herd veterinarians. Two veterinary clinics specializing in dairy practice in British Columbia, Canada, and 21 of their client dairy farms participated in the project. Following a meeting in which calf colostrum management was discussed between farmers and their herd veterinarian, participant interviews were conducted. Separate interviews were conducted for the farmers (n = 27 farmers from 21 farms) and their herd veterinarians (n = 7, with 1 to 5 farms that each vet worked with enrolled in the study) using tailored semi-structured question guides. Interviews (n = 42) were transcribed and coded following inductive thematic analysis methodology. The themes identified included strategies for farmers, veterinarians, and calf buyers, as well as contexts that influenced the dairy farmers' internal motivation to provide good calf care. Results indicated that farmers could optimize their calf management through fostering engagement of calf care personnel or by enlisting technology. Veterinarians could provide support to farms by being actively involved in calf monitoring, assisting in developing operating protocols, and setting goals, and especially by using farm-specific data to guide their management recommendations. Calf buyers could communicate with and provide accountability to farmers and improve their purchasing strategies to encourage farms to raise more vigorous surplus calves. Farmers' personal values, social networks, and relationships with different dairy industry stakeholders influenced their concern about the standards of their calf care practices. These findings provide guidance on how dairy farmers could achieve or be prompted to achieve improvements in their calf care practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".