Australian and New Zealand Veterinary Students’ Opinions on Animal Welfare and Ethical Issues Concerning Animal Use within Sport, Recreation, and Display
Bibliographic record
Abstract
Animals used for sport, recreation and display are highly visible and can divide community attitudes. The study of animal welfare and ethics (AWE) as part of veterinary education is important because it is the responsibility of veterinarians to use their scientific knowledge and skills to promote animal welfare in the context of community expectations. To explore the attitudes of veterinary students in Australia and New Zealand to AWE, a survey of the current cohort was undertaken. The survey aimed to reveal how veterinary students in Australia and New Zealand rate the importance of five selected AWE topics for Day One Competences in animals used in sport, recreation and display and to establish how veterinary students' priorities were associated with gender and stage of study. The response rate (n = 851) across the seven schools was just over 25%. Results indicated little variation on ratings for topics. The topics were ranked in the following order (most to least important): Pushing of animals to their physiologic/behavioral limits; ownership/responsibility; euthanasia; educating the public; and behavior, selection, and training for sport and recreation displays. In contrast to related studies, ratings were not associated with stage of study and there were few differences associated with gender. More females rated the pushing of animals to physiologic/behavioral limits as extremely important than did males ( p < .001). The role of veterinarians in advocating for and educating the public about the welfare of animals used in sport, recreation and display merits further discussion.
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 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".