Perceptions of on-farm emergency slaughter for dairy cows in British Columbia
Bibliographic record
Abstract
Some jurisdictions permit on-farm emergency slaughter (OFES) as one end-of-life option for dairy cows and other animals that cannot be transported humanely but are deemed fit for human consumption. Anecdotal reports suggest that OFES is controversial among dairy industry professionals, but to date their perceptions of OFES have not been studied systematically. Twenty-five individual interviews and 3 focus groups with 40 dairy producers, veterinarians, and other professionals in British Columbia, Canada, revealed positive and negative perceptions of OFES influenced by (1) individual values, (2) the perceived operational legitimacy of OFES, and (3) concern over social responsibility and public perception of the dairy industry. Study participants valued cow welfare but were divided on whether OFES quickened or delayed death for injured animals. Views on the operational legitimacy of OFES varied because of different perceptions and concerns regarding regulatory, veterinary, and meat inspector oversight, a possible conflict of interest for veterinarians, and concerns over carcass hygiene and transport. Whereas many appreciated that OFES prevented transport of compromised cows, others saw OFES as merely a stopgap measure. Seven recommended actions could address concerns while retaining the benefits of OFES: (1) specifying precise timing parameters for OFES, (2) clarification of allowable cow conditions for OFES, (3) consultation with dairy industry professionals if OFES is to be expanded, (4) more proactive culling and the development of euthanasia protocols on farms, (5) the designation of veterinarians as the first point of contact in the OFES process, (6) veterinarian training on animal inspection and allowable conditions for OFES, and (7) the use of proper procedures and equipment during the OFES process to ensure food safety.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".