Distributive Veterinary Clinical Education: A Model of Clinical-Site Selection
Bibliographic record
Abstract
The distributive model at the Western University of Health Sciences College of Veterinary Medicine (WesternU-CVM) utilizes third-party clinical sites rather than a traditional on-campus teaching hospital during years 3 and 4 of the curriculum. All veterinary schools are required by the American Veterinary Medical Association's accreditation standards to ensure that students are exposed to a diverse case load of sufficient number with active participation in the diagnostic work-up and treatment of patients. With one centralized teaching hospital, monitoring this aspect of the student experience is relatively straightforward. The distributive model of clinical veterinary education poses several challenges not encountered in a teaching hospital due to the number of clinical sites involved in delivering the curriculum. This article describes a clinical-site and preceptor selection process and the guidelines currently used to evaluate whether clinical sites and preceptors are suitable for initial inclusion in the program at WesternU-CVM. Outcomes data regarding the number and variety of student case exposures, student involvement in case management, and student evaluations of clinical experience are presented. These data suggest that the recruitment and selection process described here results in diverse and ample case-load exposure opportunities in a distributive model of veterinary education.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".