Views About and from International Medical Graduates’ General Practitioner Training in the United Kingdom
Bibliographic record
Abstract
International medical graduates (IMGs) make up a significant proportion of general practitioners (GPs) in high-income countries such as the United Kingdom (UK), the United States of America (USA), Australia, and Canada. This paper compares views about IMGs with their own views in relation to the timing of GP placements in GP specialty training programs in the UK. It presents an inductive thematic analysis of focus groups with GP specialty trainers and trainees (149 participants across 32 focus groups), examining opinions about the ideal timing of GP placements. Trainers and home graduates argued that for home graduates, the ideal sequence depends on the trainee’s previous experience. They also suggested that IMGs should start in a hospital placement to develop familiarity with the healthcare system. In contrast, most IMGs expressed a preference for starting in a GP placement, so that they can gain an understanding of the requirements of their specialty as early as possible. There is a contrast between what IMGs said about themselves and the views shared by trainers and home graduates. This highlights the need to involve IMGs in the design of support programs targeted towards them. Recommendations include tailoring training to account for individual career paths and providing training about the healthcare system before the start of the first placement. This could improve the efficiency of GP training programs at a time of extreme pressure on healthcare systems and training providers.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".