A Comparison of Veterinary Students Enrolled and Not Enrolled in an Animal-Welfare Course
Bibliographic record
Abstract
An online survey was conducted to compare 46 veterinary students who previously enrolled in a discussion-based animal-welfare elective with 45 veterinary students who did not take the course. Students were asked a series of questions about their attitudes toward animal welfare and were presented with animal-use scenarios that had not previously been discussed in the elective course: greyhound racing, veal calf production, and the use of genetically engineered mice in research. For each scenario, students' actual knowledge was scored on the basis of open-ended factual questions. Students were also asked how comfortable they were with educating themselves about each topic and to describe factors they would use to evaluate the welfare of animals in each scenario. Factors were classified as being associated with (a) biological functioning, (b) ability to exist in a natural state, or (c) measures of affective state or feelings. There was no significant difference in actual knowledge of the three scenarios between students who took the course and those who did not. Students who took the course were significantly more likely to be comfortable about educating themselves on each of the three animal-use scenarios and scored significantly higher in identifying welfare-affecting factors than students who did not take the course. The results suggest that this approach to instruction is an effective way to teach veterinary students about how to educate themselves about animal-welfare issues and to increase their confidence in appropriately evaluating novel animal-welfare topics.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| opus | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".