Companion Animal Cadaver Donation for Teaching Purposes at Veterinary Medicine Colleges: A Discrete Choice Experiment
Bibliographic record
Abstract
Veterinary training programs rely on animal cadavers for a variety of important educational activities, yet ethical sourcing can present considerable challenges. Public sentiment has rendered traditional sources (e.g., euthanized shelter animals or purpose-bred animals) increasingly tenuous throughout the United States, leaving many schools to search for alternatives. One such alternative is to establish a cadaver donation program, with a handful of institutions implementing such programs in recent years. Still, there have been few to no studies evaluating the factors that influence pet owners' decisions about whether to participate that could inform the establishment of such programs to date. In the present study, a nationally (United States) representative sample of current and potential dog and cat owners was asked to complete a survey capturing various demographic factors as well as their existing attitudes toward both veterinary medicine and veterinary education in addition to selecting among hypothetical cadaver donation programs with varying attribute levels in a blocked, orthogonal, fractional factorial discrete choice experiment to determine the characteristics that correlate with higher participation rates. Although initial interest was strong, our results suggest that younger pet owners, individuals with more formal education, and individuals with positive relationships with their current veterinarian are most likely to participate in a donation program. Concerningly, however, dog owners were somewhat less likely than other respondents to participate. The return of pet ashes was the most important attribute to respondents, suggesting that cadaver donation administrators should consider inclusion of this service to maximize participation.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".