A Benchmark Survey of the Delivery of Clinical Education in Small Animal Primary-Care Clinical Programs Among Member Institutions of the American Association of Veterinary Medical Colleges
Bibliographic record
Abstract
While primary-care clinical rotations are well established and have been incorporated into veterinary colleges over the past 50 years, standardization of teaching small animal primary care across veterinary colleges is unknown. The purpose of this study was to explore and document variations and similarities in the delivery of small animal primary-care clinical education curricula among member programs of the American Association of Veterinary Medicine Colleges (AAVMC). A comprehensive, 114-question online survey was conducted, comprising seven sections, including Rotation Logistics; House Officers; Procedures Performed; Rounds; Spectrum of Care; Diversity, Equity, and Inclusion; Assessment; Leadership Roles; and Research. Of the 52 AAVMC institutions worldwide at the time of the survey, 69% (36/52) of programs responded, of which 86% (31/36) met inclusion criteria and were retained for analysis. Results revealed primary-care services report seeing a mean of 75.84 cases per week (median 70, range 20–180, SD 37.34, n = 29), which serve as educational experiences for veterinary students rotating through the service, including the practice of hands-on clinical skills (including surgical procedures), discussing “flexible treatment care options” with clients, and actively leading cases. Length and size of a primary-care rotation varied with a mean duration of 3 weeks (median 2, range 2–12, SD 2.02, n = 29) and mean of 10 students (median 8.5, range 5–36, SD 5.87, n = 28) per rotation. This study highlights the current state of primary-care veterinary clinical education and provides descriptive data that might serve as a basis to guide future development of primary-care curricula across clinical programs.
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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 | 0.022 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".