An Approach to Teaching Animal Welfare Issues at The Ohio State University
Bibliographic record
Abstract
Despite the growing importance of animal welfare and the critical role of the veterinary profession, animal welfare is not formally taught in many veterinary curricula. In addition, veterinary students are often not exposed to current contentious animal welfare issues, which are subject to much debate and often proposed regulation. To address this deficiency in our curriculum at The Ohio State University College of Veterinary Medicine, we have developed a course titled "Contemporary Issues in Animal Welfare." Our specific objectives for the course are: 1) to provide students with the opportunity to objectively evaluate and discuss current issues in the welfare of animals as companions, and in the industries of agriculture, science, education, conservation, and entertainment; 2) to increase students' awareness of current important animal welfare issues; and 3) to develop students' skills in the critical evaluation of written and visual material used in the scientific literature and lay press. We hope that, over time, this teaching model will be considered a means to educate veterinary students about animal welfare issues in other veterinary curricula.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".