Symposium review: Considerations for the future of dairy cattle housing: An animal welfare perspective
Bibliographic record
Abstract
Many contemporary dairy cattle housing practices are at odds with societal perceptions of positive animal welfare. The public (i.e., those external to the dairy industry) typically emphasizes the importance of naturalness for dairy cattle, such as through provision of pasture, freedom of movement, and the ability to interact socially with conspecifics. Yet, in the United States, the majority of lactating dairy cattle are reportedly housed without any access to pasture, and almost 39% of dairy farms use tiestalls, which restrict movement and social interactions. In addition to being in conflict with public expectations, a lack of pasture access and restrictive housing systems are also in conflict with the animals' own motivations, which can adversely affect their welfare. For example, dairy cattle are highly motivated to access pasture and show a reduction in oral stereotypies when allowed on pasture after periods of tethering. Calves housed without social contact have cognitive deficits and exhibit increased fear responses to novelty. We argue that the long-term sustainability of the dairy industry will depend on the extent to which housing systems reflect public concerns and the animals' priorities. The adoption of technologies, such as automated feeders and remote monitoring systems, may represent a means to practically promote the animals' natural behavior while simultaneously improving individualized care. Although older generations of the public may consider technological solutions to be a further deviation from naturalness and a departure from dairy farming's agrarian roots, the definition of "naturalness" for younger generations may well have expanded to include technology. As the buying power shifts to these younger generations, the adoption of technologies that promote natural cattle behaviors may be one means toward reconciling the disconnect between public perceptions of animal welfare and contemporary dairy farming practices.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".