The pipeline flows through pre-clerkship – the early exposure of medical learners to rural healthcare
Bibliographic record
Abstract
Introduction: We sought to investigate the influence of a 1-week rural clinical placement during pre-clerkship on participants' decisions to pursue subsequent rural clinical training and rural practice, and the factors which influenced participants to participate in the placement Methods: A survey was sent to all physicians who: participated in the Rural Ontario Medical Program's (ROMP) 1-week ROMP Week placement between 1999 and 2012; had completed postgraduate training; and were currently practicing medicine in Ontario. Survey items were rated on a Likert scale, and Mann-Whitney U Testing performed to identify differences between groups. Results: Of the 407 surveys distributed, 154 were completed. 23.2% of physicians reported having a rural background, 59.2% completed a rural clinical rotation during clerkship or residency, and 21.3% currently practiced in rural communities at the time of survey completion. The learning opportunity and clinical experiences in rural healthcare were reported as the primary motivating factors for participating in ROMP Week. Better learning opportunities in rural rotations, meeting the communities' needs, and support from rural communities were the primary motivating factors for participating in subsequent rural clinical rotations. Physicians practicing in rural communities at the time of survey completion had higher ratings of attraction to rural communities and desire to gain rural clinical experience as reasons for participating in ROMP Week. Conclusion: A majority of ROMP Week participants subsequently undertook rural clinical rotations, and the proportion of participants currently practicing as rural physicians exceeds the proportion of Canadian physicians practicing in rural communities as a whole. 54% of respondents practicing in a rural community at the time of survey completion did not have a rural background, and ROMP Week may have been their first exposure to rural medical practice. Rural experiences during preclerkship offer an opportunity to increase the number learners in the rural physician pipeline.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".