Euthanasia Education in Veterinary Schools in the United States
Bibliographic record
Abstract
Euthanasia of animals plays a significant role in veterinary practices and is a pivotal experience for veterinarians and their clients. It is good animal welfare to have a humane method of euthanasia, correctly applied, and a well-educated individual regarding such techniques. The purpose of this research was to determine how US veterinary medicine schools are preparing students to perform euthanasia. A survey of the 30 US veterinary schools was electronically mailed by the American Association of Veterinary Medical Colleges (AAVMC) in the fall of 2019, with a return rate of 10. Findings revealed that the average number of hours devoted to euthanasia methods and techniques was 2.8, yet euthanasia facilitation was considered a core competency by all schools responding. Not all veterinary students perform or are present for euthanasia. The most frequent method for teaching euthanasia was intracardiac and intravenous with dogs, cats, horses, livestock, and exotics. Whichever method of euthanasia is used, personnel performing euthanasia must be trained, knowledgeable, and proficient in the chosen techniques. The findings in this article suggest, however, that euthanasia techniques are inconsistent, and potentially incomplete, and that veterinary schools should consider incorporating more advanced euthanasia training programs into the curriculum.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".