Do students from rural backgrounds engage in rural family practice more than their urban‐raised peers?
Bibliographic record
Abstract
INTRODUCTION: In a previous prospective study, students from rural backgrounds were found to be significantly more likely to consider rural practice than their urban-raised peers. The purpose of this study was to determine whether the students with rural backgrounds who participated in the original investigation were more likely than their urban-raised peers to be currently engaged in rural family practice. METHOD: In Canada, family doctors have the greatest opportunity to practise in rural communities. Consequently, rural and urban background students from the original study who entered the discipline of family medicine as a career were identified for practice location follow-up. Participants were categorised as either rural (population less than 10 000) or urban practitioners according to the population of the community in which they practised. The proportion of rural and urban background students engaged in rural or urban practice was analysed using chi-square and relative risk probability. RESULTS: A total of 78 students from the original cohort were found to be practising family medicine; 22 of them had been rurally raised. Seven (32%) of the rural background students were practising in a rural community, compared to 7 (13%) of the 56 urban background students (RR = 2.55; P < 0.05). CONCLUSIONS: Rural background students who went on to complete family medicine residency training were approximately 2.5 times more likely to be engaged in rural practice than their urban-raised peers. Altering medical school admission policy to recruit more rural background applicants should be part of a multi-dimensional approach to increasing the number of rural practitioners.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".