Using Mobile Polling to Teach Animal Ethics to Large Audiences: A Case Study of First-Year Veterinary Students’ Personal Views
Bibliographic record
Abstract
Research has demonstrated that educating veterinary students in animal ethics helps them address moral dilemmas in their later careers. Teaching about animal ethics dilemmas to large student groups is challenging. Therefore, a polling series was created for first-year veterinary students at Ghent University, Belgium. Over the course of three theoretical sessions and during four consecutive academic years, students answered four questions about which animals they have at home, prioritization of animal versus owner interests, motivations for studying veterinary medicine, and eating patterns. Poll results were used to discuss student views in an applied session. The voluntary polls were a success, with more than half of the students taking part and with the participation rate increasing over four years. Findings indicate that animal ethics topics were more likely to elicit a response from students than veterinary ethics topics. This trend persisted in applied sessions, where students found it easier to discuss and substantiate animal ethics dilemmas compared to veterinary ethics dilemmas. In conclusion, discussing polling results on animal ethics dilemmas can help first-year veterinary students develop ethical awareness, personal identity, and decision-making skills.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".