Faculty Development for a New Curriculum: Implementing a Strategy for Veterinary Teachers within the Wider University Context
Bibliographic record
Abstract
Faculty development in veterinary education is receiving increasing attention internationally and is considered of particular importance during periods of organizational or curricular change. This report outlines a faculty development strategy developed since October 2012 at the University of Bristol Veterinary School, in parallel with the development and implementation of a new curriculum. The aim of the strategy is to deliver accessible, contextual faculty development workshops for clinical and non-clinical staff involved in veterinary student training, thereby equipping staff with the skills and support to deliver high-quality teaching in a modern curriculum. In October 2014, these workshops became embedded within the new University of Bristol Continuing Professional Development scheme, Cultivating Research and Teaching Excellence. This scheme ensures that staff have a clear and structured route to achieving formal recognition of their teaching practice as well as access to a wide range of resources to further their overall professional development. The key challenges and constraints are discussed.
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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 | 0.060 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".