Satellite Teaching Hospitals and Public–Private Collaborations in Veterinary Medical Clinical Education
Bibliographic record
Abstract
Veterinary teaching hospitals (VTHs) are facing more and greater challenges than at any time in the past. Changes in demand, expanding information, improving technology, an evolving workforce, declining state support, and an increasingly diverse consumer base have combined to render many traditional VTH modes of operation obsolete. In pursuit of continued success in achieving their academic mission, VTHs are exploring new business models, including innovative collaborations with the private sector. This report provides details on existing models for public-private collaboration at several colleges and schools of veterinary medicine, including those at Kansas State University, Purdue University, the University of Florida, and Tufts University. Although each of these institutions' models is unique, several commonalities exist, related to expansion of the case load available for teaching, the potential positive impact on recruitment and retention of clinical faculty, and the potential for easing financial pressures on the associated VTH. These new models represent innovative approaches that work to meet many of the key emerging challenges facing VTHs today.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".