A Rural and Regional Community Multi-Specialty Residency Training Network Developed by the University of Western Ontario
Bibliographic record
Abstract
BACKGROUND: Traditionally, specialty vocational/residency training is totally done in tertiary care university-hospital settings, making it very difficult for specialty residents to learn about the joys and challenges of rural and regional patient care. DESCRIPTION: The University of Western Ontario's Multi-Specialty Community Training Network (MSCTN) was developed to provide specialty residents with the opportunity to do part of their postgraduate vocational training in rural and regional practice settings. The network involves 10 medical school departments/divisions and 7 rural/regional communities. From 1997 to 2004, 174 residents have completed 287 months of rural/regional training. EVALUATION: Residents rated their overall learning experience at 6.41 on a 7-point scale. Nineteen of the 39 graduating residents have chosen to practice in rural and regional underserviced communities. CONCLUSION: Rural/regional specialty postgraduate vocational training rotations can provide excellent learning experiences. Preliminary results indicate that this exposure encourages many specialty residents to establish rural and regional practices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".