Attitudes of Veterinary Students at One US College toward Factors Relating to Farm Animal Welfare
Bibliographic record
Abstract
RATIONALE FOR STUDY: The American Veterinary Medical Association's policy states that veterinarians are obliged to promote good animal welfare. In order to establish how compatible the attitudes of future veterinarians in one North American Veterinary College were with the promotion of good animal welfare, students were surveyed with respect to their opinions about the humaneness of commonly employed agricultural procedures (e.g., hot branding) and their beliefs about the cognitive ability of various domesticated species. METHODOLOGY: A Web-based questionnaire was made available to all veterinary students at Cornell University. Descriptive summary data were collected with regards to students' perceptions of the cognitive abilities of six different domesticated species. Students were also asked if they considered certain agricultural procedures to be humane for each of these species. The data were analyzed with respect to students' future career goals. Chi-squared tests and nonparametric statistical techniques were used to examine differences between species and desired career goals. RESULTS AND CONCLUSIONS: Veterinary students were more likely to believe that dogs and cats had cognitive abilities than farm animals did. Students considered various procedures to be more humane for farm mammals than for dogs and cats. Students aspiring to work with food animals considered more procedures to be humane for all species than did students aspiring to work with small animals. The inconsistency of students' attitudes for different species has implications for veterinary education and animal welfare. Scientific fields integral to understanding animal welfare may need to be emphasized within the veterinary educational 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 | 0.006 | 0.008 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".