Brazilian Citizens: Expectations Regarding Dairy Cattle Welfare and Awareness of Contentious Practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The primary aim of this study was to explore attitudes of urban Brazilian citizens about dairy production. A secondary aim was to determine their knowledge and attitudes about four potentially contentious routine dairy cattle management practices: early cow-calf separation; zero-grazing; culling of newborn male calves; and dehorning without pain mitigation. To address the first aim 40 participants were interviewed using open-ended semi-structured questions designed to probe their views and attitudes about dairy production in Brazil, and 300 participants answered a questionnaire that included an open-ended question about the welfare of dairy cattle. Primary concerns reported by the participants centered on milk quality, which included the rejection of any chemical additives, but also animal welfare, environmental and social issues. The interviewees rarely mentioned animal welfare directly but, when probed, expressed several concerns related to this topic. In particular, participants commented on factors that they perceived to influence milk quality, such as good animal health, feeding, clean facilities, and the need to avoid or reduce the use of drugs, hormones and pesticides, the avoidance of pain, frustration and suffering, and the ability of the animals to perform natural behaviors. To address our second aim, participants were asked questions about the four routine management practices. Although they self-reported being largely unaware of these practices, the majority of the participants rejected these practices outright. These data provide insight that animal welfare may be an important issue for members of the public. Failure to consider this information may increase the risk that certain dairy production practices may not be socially sustainable once lay citizens become aware of them.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it