Building on Existing Models from Human Medical Education to Develop a Communication Curriculum in Veterinary Medicine
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
Communication is a core clinical skill of veterinary medicine and one that needs to be taught and learned to the same degree as other clinical skills. To provide this education and essential expertise, veterinary schools in many countries, especially including North America, the United Kingdom, and Australia, have begun to develop programs and communication curricula. Human medical education, however, has 30 years' experience in developing communication curricula, and is thus an excellent resource upon which veterinary educators can build and shape their own communication programs. This article describes a skills-based communication course that has been successfully implemented for veterinary medical education at Ontario Veterinary College (OVC) and was based on the University of Calgary Faculty of Medicine's well-established program. The Calgary-Cambridge Guides and supporting textbooks provide the scaffolding for teaching, learning, and evaluation in both programs. Resources such as space and materials to support the OVC program were also patterned after Calgary's program. Communication skills, and the methods for teaching and learning them, are equally applicable for the needs of both human medicine and veterinary medicine. The research evidence from human medicine is also very applicable for veterinary medicine and provides it the leverage it needs to move forward. With this extensive base available, veterinary medicine is in a position to move communication skills training forward rapidly.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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 it