Invited review: Effects of group housing of dairy calves on behavior, cognition, performance, and health
Bibliographic record
Abstract
Standard practice in the dairy industry is to separate the calf and dam immediately after birth and raise calves in individual pens during the milk-feeding period. In nature and in extensive beef systems, the young calf lives in a complex social environment. Social isolation during infancy has been associated with negative effects, including abnormal behavior and developmental problems, in a range of species. Here, we review empirical work on the social development of calves and the effects of social isolation in calves and other species; this evidence indicates that calves reared in isolation have deficient social skills, difficulties in coping with novel situations, as well as specific cognitive deficits. We also review the practices associated with group housing of dairy calves, and discuss problems and suggested solutions, especially related to cross-sucking, competition, aggression, and disease. The studies reviewed indicate that social housing improves solid feed intakes and calf weight gains before and after calves are weaned from milk to solid feed. Evidence regarding the effects of social housing on calf health is mixed, with some studies showing increased risk of disease and other studies showing no difference or even improved health outcomes for grouped calves. We conclude that there is strong and consistent evidence of behavioral and developmental harm associated with individual housing in dairy calves, that social housing improves intakes and weight gains, and that health risks associated with grouping can be mitigated with appropriate management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".