Fifty Years of Evolving Partnerships in Veterinary Medical Education
Bibliographic record
Abstract
The Association of American Veterinary Medical College's (AAVMC's) role in the progression of academic veterinary medical education has been about building successful partnerships in the US and internationally. Membership in the association has evolved over the past 50 years, as have traditions of collaboration that strengthen veterinary medical education and the association. The AAVMC has become a source of information and a place for debate on educational trends, innovative pedagogy, and the value of a diverse learning environment. The AAVMC's relationship with the American Veterinary Medical Association Council on Education (AVMA COE), the accreditor of veterinary medical education recognized by the United Sates Department of Education (DOE), is highlighted here because of the key role that AAVMC members have played in the evolution of veterinary accreditation. The AAVMC has also been a partner in the expansion of veterinary medical education to include global health and One Health and in the engagement of international partners around shared educational opportunities and challenges. Recently, the association has reinforced its desire to be a truly international organization rather than an American organization with international members. To that end, strategic AAVMC initiatives aim to expand and connect the global community of veterinary educators to the benefit of students and the profession around the world. Tables in this article are intended to provide historical context, chronology, and an accessible way to view highlights.
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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 | 0.021 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".