Accreditation of Veterinary Schools in Australia and New Zealand
Bibliographic record
Abstract
Veterinary schools in Australia and New Zealand are assessed for accreditation purposes every six years by the Veterinary Schools Accreditation Advisory Committee (VSAAC), which is a standing committee of the Australasian Veterinary Boards Council (AVBC).1 Prior to undertaking an assessment, VSAAC requests a Self Evaluation Report from the school and subsequently spends a week on site to collect additional information. The committee also takes into consideration other quality assurance procedures within the university and aims for a process that complements other evaluation activities. Internal evaluation procedures within VSAAC are designed to reflect the process and outcomes of each visit and lead to annual revisions of the publication Policies, Procedures and Guidelines publication. The committee has close links with the Royal College of Veterinary Surgeons (RCVS), and there is a routine exchange of observers on all visits in the United Kingdom and Australasia. In recent years VSAAC has become increasingly interested in looking at ways to place greater emphasis on the outcomes of veterinary education and, eventually, to reduce our reliance on input measures. There has been good progress in identifying desirable attributes for veterinary graduates, but further work is needed to establish the reliability of assessment procedures. The Australasian accreditation system is very supportive of recent moves to achieve greater compatibility of veterinary accreditation systems in different parts of the world because we believe it has the potential to assist globalization of animal disease control and veterinary education.
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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 | 0.017 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".