Combined research and clinical learning make rural summer studentship program a successful model
Bibliographic record
Abstract
CONTEXT: Many medical schools would like to provide students with opportunities to learn and perform practical research and to have positive rural learning experiences. Rural physicians often have research ideas, but may lack the skills or assistance to perform the research. PROGRAM DESCRIPTION: The unique Rural Summer Studentship Program (RSSP) at The University of Western Ontario (Western) places students with preceptors in small and mid-sized communities throughout Southwestern Ontario where they have an opportunity to perform rural health research, combined with clinical learning, for 8 weeks in the summer after the first or second year of medical school. Secretarial coordination, research assistant support and senior faculty supervision were provided. OUTCOMES: From 1999-2003 inclusive, 44 students have participated including eight who participated over two summers. Projects were carried out in more than 20 communities with over 30 preceptors. Already, two students have had their research published in peer-reviewed journals and six have presented at major conferences. Participating students indicated an increase in interest in rural and regional medicine and in their knowledge of rural and regional medicine and patient care. They rated the value of RSSP highly as part of their medical education, even compared with other electives/selectives. CONCLUSION: The RSSP model developed at Western provides a highly rated, successful combination of supported medical student research and clinical learning with preceptors in small and mid-sized communities.
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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 | 0.006 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".