Attitudes of Canadian beef producers toward animal welfare
Bibliographic record
Abstract
Abstract Commercial beef production in western Canada involves raising cows and calves on large tracts of grassland, plus grain-based ‘finishing’ of animals in outdoor feedlots. This study used open-ended, semi-structured interviews to explore views on animal welfare of 23 commercial beef producers in this system. Although wary of the term ‘animal welfare’, participants understood the concept to encompass three well-known elements: (i) basic animal health and body condition; (ii) affective states (comfort, contentment, freedom from hunger or thirst); and (iii) the ability to live a ‘natural’ life. Participants attached importance to protecting animals from natural hardships (extreme weather, predators), yet many regarded some degree of natural challenge as acceptable or even positive. Quiet rumination was uniformly regarded as indicating contentment. Avoiding ‘stress’ was seen as a central goal, to be achieved especially by skilful handling and good facilities. Invasive procedures (branding, castration, de-horning) were recognised as painful but were accepted because they were seen as: (i) necessary for regulatory or management reasons; (ii) satisfactory trade-offs to prevent worse welfare problems such as aggression; or (iii) sufficiently short-term to be relatively unimportant. Other issues — including poor facilities, rough or excessive handling, poor nutrition, and failure to protect health — were regarded as more serious welfare concerns. While feeling constrained by low profits, participants saw good welfare as crucial to profitability. Participants uniformly expressed an ethic of care, enjoyment of working with animals, and varying degrees of willingness to sacrifice personal comfort for animal well-being. We argue that animal welfare policy and advocacy are likely to be more successful in engaging producers if they acknowledge and address producers’ views on animal welfare.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".