Survey of colleges and schools of veterinary medicine regarding education in complementary and alternative veterinary medicine
Bibliographic record
Abstract
OBJECTIVE: To obtain information on educational programs offered in complementary and alternative veterinary medicine (CAVM) among AVMA Council on Education (COE)-accredited colleges and schools of veterinary medicine. DESIGN: Survey. SAMPLE: 41 COE-accredited colleges and schools of veterinary medicine. PROCEDURE: A questionnaire was e-mailed to academic deans at all COE-accredited colleges and schools of veterinary medicine. RESULTS: Responses were received from 34 of 41 schools: 26 in the United States, 2 in Canada, 3 in Australia and New Zealand, and 3 in Europe. Sixteen schools indicated that they offered a CAVM course. Nutritional therapy, acupuncture, and rehabilitation or physical therapy were topics most commonly included in the curriculum. One school required a course in CAVM; all other courses were elective, most of which were 1 to 2 credit hours. Courses were usually a combination of lecture and laboratory; 2 were lecture only, and 1 was laboratory only. Of the 18 schools that reported no courses in CAVM, many addressed some CAVM topics in other courses and 4 indicated plans to offer some type of CAVM course within the next 5 years. CONCLUSIONS AND CLINICAL RELEVANCE: The consensus among survey respondents was that CAVM is an important topic that should be addressed in veterinary medical education, but opinions varied as to the appropriate framework. The most common comment reflected strong opinions that inclusion of CAVM in veterinary medical curricula must be evidence-based. Respondents indicated that students should be aware of CAVM modalities because of strong public interest in CAVM and because practitioners should be able to address client questions from a position of knowledge.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".