A Global Survey of the Views of Practicing Companion Animal Veterinarians on Their Undergraduate Curriculum and Their Access to Continuing Education Resources
Bibliographic record
Abstract
A global survey was developed to gain insight into the opinion of companion animal veterinarians about their undergraduate education and their access to continuing education on the following topics: client communication, animal welfare, surgical techniques, human-animal bond, dentistry, animal behavior, and zoonotic disease/epidemiology. In 2016, the survey was distributed via SurveyMonkey® in five languages to companion animal veterinarians around the world. A total of 1,167 respondents returned the survey. The distribution of survey responses differed by geographic region (number of respondents in parentheses; where respondents work/have been trained): Europa (including the Russian Federation, 359/423), Asia (311/205), North America (77/89), South America (24/16), Africa (46/41), and Oceania (147/167). The results were strongly influenced by a large number of respondents (in parentheses) who graduated in the Russian Federation (180/162), Australia (133/154), Israel (136/82), the Netherlands (64/64), the United Kingdom of Great Britain and Northern Ireland (36/46), and the United States of America (46/44). On the basis of the responses, all topics were poorly covered or not taught, except for surgical techniques and zoonotic disease/epidemiology, which were covered adequately or well. However, there were country and geographic regional differences. This was also true for continuing education resources, which were-in addition to countries and geographic regions-also influenced by the educational topic. As already stated by Dhein and Menon in 2003, time away from the practice, travel distance, and expense may be reasons why companion animal veterinarians do not follow continuing education. Online continuing education could fill in the gap and is more time and cost-efficient.
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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 | 0.003 | 0.005 |
| 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) | 0.000 | 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 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".