Undergraduate teaching in UK general practice: a geographical snapshot
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
BACKGROUND: Learning in general practice is an essential component of undergraduate medical education; currently, on average, 13% of clinical placements in the UK are in general practice. However, whether general practice can sustainably deliver more undergraduate placements is uncertain. AIM: To identify the geographical distribution of undergraduate teaching practices and their distance from the host medical school. DESIGN AND SETTING: National survey of all medical schools in the UK. METHOD: All 33 UK medical schools were invited to provide the postcodes of their undergraduate teaching practices. These were collated, de-duplicated, and mapped. The distance in kilometres and journey times by car and public transport between each medical school and its teaching practices was estimated using Transport Direct (www.transportdirect.info). The postcodes of every practice in the UK were obtained from the UK's health departments. RESULTS: All 33 UK medical schools responded; 4392 practices contributed to teaching, with a median (minimum-maximum) of 142 (17-385) practices per school. The median (minimum-maximum) distance between a school and a teaching practice was 28 km (0-1421 km), 41 (0:00-23:26) minutes' travel by car and 1 hour 12 (0:00-17:29) minutes' travel by public transport. All teaching practices were accessible by public transport in one school and 90-99% were in a further four schools; 24 schools had >20% of practices that were inaccessible by public transport. CONCLUSION: The 4392 undergraduate teaching general practices are widely distributed and potentially any practice, no matter how isolated, could contribute to undergraduate education. However, this is, at the price of a considerable travel burden.
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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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