Bibliographic record
Abstract
The sustainability of the traditional university-owned and -operated veterinary teaching hospital has been discussed for many years. Concerns around the shortage and lack of diversity of clinical faculty, financial sustainability, and suitability of secondary and tertiary case load for the development of Doctor of Veterinary Medicine students' Day One Competences are perennial issues. Consequently, many schools have been looking at alternative ways of delivering veterinary clinical education. This article provides a conceptual framework for evaluating the delivery of veterinary clinical education, providing putative advantages and disadvantages of each model for further empirical investigation. Four different models are proposed-owner, third party, embedded distributive, and fully distributive-that can broadly be defined along two dimensions: the degree of integration of the clinical enterprise with the academic enterprise and the degree of authority of the dean/head of school with respect to clinical enterprise governance and their role in budgetary, investment, and hiring decisions. The author offers a typology that may assist deans/heads of schools make strategic decisions about the mode of delivery of veterinary clinical education for their school.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".