Reconsidering the Lecture in Modern Veterinary Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Those teaching in the higher-education environment are now increasingly meeting with larger cohorts of students. The result is additional pressure on the resources available and on the teacher and learners. Against this backdrop, discussions and reflections took place between a practitioner, within a UK veterinary school, and an educational researcher with extensive experience in observing teaching in veterinary medicine. The result was an examination of the lecture as a method of teaching to consider how to resolve identified challenges. The focus of much of the literature is on technical aspects of teaching and learning, reverting to a range of tips to resolve particular issues recognized in large-group settings. We suggest that while these tips are useful, they will only take a practitioner so far. To be able to make a genuine connection to learners and help them connect directly to the discipline, we need to take account of the emotional aspects of our role as teachers, without which, delivery of knowledge may be undermined.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it