Developing and Evaluating Animal Welfare Case Studies for Veterinary Students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Within veterinary education, case studies promote critical thinking and provide an opportunity for students to solve problems they may encounter after graduation. Cases are useful for many disciplines within veterinary medicine, but are particularly beneficial for teaching complex, multidisciplinary topics such as animal welfare. There are several resources within the literature describing methods for creating effective cases for a wide variety of educational disciplines. However, animal welfare educators are not often provided guidance on how to develop their own cases and seldom get the opportunity to receive feedback on cases they have created. The goal of this article is to provide animal welfare educators with a resource they can use when creating their own case studies for veterinary students. Our specific objective is to describe the process used to develop and evaluate farm animal welfare case studies for veterinary students.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it