The Challenges and Issues of Undergraduate Student Retention and Attainment in UK Veterinary Medical Education
Bibliographic record
Abstract
Student retention and attainment has recently been identified as a key area for development in veterinary medical education enquiry. Woodfield's research on retention and attainment across the UK disciplines has yielded some unique information about the challenges and issues of students who study veterinary medicine and related subjects. The present literature review aims to expand on Woodfield's findings and explain important issues about retention and attainment across veterinary medicine. Overall, the subject of retention and attainment in undergraduate veterinary medical education needs a great deal more empirical attention, such as data on the retention and attainment of mature and widening access students, and the effects of students being placed at remote locations during their studies. Our findings also cover some unsurprising issues: the dominance of women in a profession that is principally lead by men, the underrepresentation of black and minority ethnic (BME) students in veterinary medicine, and the effects of content overload in the veterinary medical curriculum. Based on data gathered by Woodfield and our investigation of the scholarly and gray literatures, we offer an overview of gaps in current knowledge and recommendations for further research.
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 | 0.004 | 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 | 0.000 |
| 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 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".