Determination of Dairy Cattle Euthanasia Criteria and Analysis of Barriers to Humane Euthanasia in the United States: Dairy Producer Surveys and Focus Groups
Bibliographic record
Abstract
There are currently no clear guidelines in the US and some other countries regarding euthanasia decision making timelines for dairy cattle that become injured or ill to the extent that recovery is unlikely or impossible. Our study aimed to identify decision making criteria and the most common factors considered when making and carrying out euthanasia decisions. Dairy producers were recruited to participate in a mailed survey (Part I, 307 completed surveys were returned) or in one of three focus groups (Part II, 8–10 producers/group, n = 24). Part I (survey): Farm owners were most commonly responsible for on-farm euthanasia and most respondents would treat and monitor compromised cattle for a majority of 15 health conditions. Responses were highly variable; for example, 6.3% and 11.7% of respondents would never euthanize a non-ambulatory cow or calf, respectively. Part II (focus groups): Three main themes (animal, human, and farm operation) were identified from discussion which focused primarily on animal welfare (16% of the discussion) and human psychology (16%). Participants expressed a desire to eliminate animal suffering by euthanizing, alongside a wide range of emotional states. Development of specific standards for euthanasia is a critical next step and more research is needed to understand the human emotions surrounding euthanasia decision making.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".