The impact of urban-based family medicine postgraduate rotations on rural preceptors/teachers
Bibliographic record
Abstract
BACKGROUND: The use of rural rotations within urban-based postgraduate programs is the predominant response of medical education to the health needs of underserved rural populations. The broader impact on rural physicians who teach has not been reported. METHODS: This study examined the personal, professional, and financial impact of a rural rotations for urban-based family medicine (UBFM) residents on Canadian rural teaching physicians. A survey was created and reviewed by community and academic rural physicians and a cohort of Canadian rural family physicians teaching UBFM residents was sampled. Survey data and free-text responses were assessed using quantitative and qualitative analyses. RESULTS: < 0.001). Rural preceptors often held contrasting attitudes towards learners with negative judgements counter-balanced by positive thoughts. Duration in practice and of teaching experience did not have a significant impact on ratings. CONCLUSION: Being a rural preceptor of UBFM residents is rewarding but also stressful. The preceptor location of training and scope of practice appears to influence the impact of UBFM residents.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".