Social housing for dairy calves: Farmer acceptance of Canadian industry-led requirements
Bibliographic record
Abstract
Research suggests that housing milk-fed calves in pairs or small groups from a young age can provide welfare benefits, leading some policymakers to encourage dairy farmers to adopt this practice. For example, Canada's industry-led Code of Practice for the Care and Handling of Dairy Cattle requires social housing for indoor-housed calves, starting in 2031. We assessed acceptance of social housing and this new Code requirement by conducting 23 interviews with 13 farmers in Alberta and British Columbia, Canada. Interview questions were designed to evaluate 8 constructs (affective attitude, burden, ethicality, opportunity costs, perceived effectiveness, self-efficacy, and trust in the Canadian Dairy Code development process) derived from the "Theoretical Framework of Acceptance." Participant acceptance varied, with some appreciating the benefits of social housing, and others citing concerns about the need for the requirement. Farmers generally thought they would be able to adopt social housing. Most participants prioritized concerns about calf health, but also considered calf socialization beneficial. However, some farmers also expressed frustration with the new Canadian Dairy Code requirement and did not feel their interests were represented in the Code development process. These findings highlight the need to address farmer concerns with new policies and practices, for example, through events that support farmers and their advisers to share successful approaches to implementation. Further research is required to better understand farmer views on representation in the development of policies that govern on-farm 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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".