A Survey of Reading, Writing, and Oral Communication Skills in North American Veterinary Medical Colleges
Bibliographic record
Abstract
In the 1989 report by the Pew National Veterinary Education Program (PNVEP), communication skills topped the list of characteristics the veterinary graduate should possess in order to function effectively in the twenty-first century. To determine the reading, writing, and oral communication requirements and opportunities in veterinary curricula in the US and Canada, and to determine the perceived communication tasks that might be commonly required of practicing veterinarians in the next century, we sent a 15-item communications skills questionnaire to the academic deans of the 31 veterinary curricula in the US and Canada. The results reinforce the importance of communication skills in veterinary medicine, as detailed by the PNVEP over 10 years ago. Based on the responses to our questionnaire and on our own experiences with veterinary medical students, we make several recommendations to enhance communication instruction in veterinary medical curricula.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".