Does a rural educational experience influence students' likelihood of rural practice? Impact of student background and gender
Bibliographic record
Abstract
CONTEXT: The family medicine clerkship at the University of Calgary is a 4-week mandatory rotation in the final year of a 3-year programme. Students are given the opportunity to experience rural practice by training at 1 of several rural practices. OBJECTIVE: To determine whether exposure to a rural educational experience changes students' likelihood of doing a rural locum or rural practice and whether student background and gender are related to these practice plans. METHOD: Clinical clerks from the Classes of 1996-2000, who trained at rural sites, responded to questionnaire items both before and after the rural educational experience. Responses to the questionnaire items and discipline of postgraduate training served as dependent variables. Student background and gender were independent variables. RESULTS: As a result of the rural educational experience all students were more likely to do a rural locum. Compared to their urban-raised peers, students from rural backgrounds reported a significantly greater likelihood of doing a rural locum and practising in a rural community, irrespective of gender or participating in a rural educational experience. There was no relationship between background and career choice. CONCLUSION: A rural educational experience at the undergraduate level increases the stated likelihood of students participating in rural locums and helps to solidify existing rural affiliations. Students with rural backgrounds have a more favourable attitude toward rural practice. This pre-post study provides further support for the preferential admission to medical school of students with rural backgrounds to help alleviate the rural physician shortage.
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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 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".