Rural physicians' skills enrichment program: A cohort control study of retention in Alberta
Bibliographic record
Abstract
OBJECTIVE: The Rural Physician Action Plan of Alberta introduced an enrichment program in 2001 to improve physician access to skills training. The objective of this study was to evaluate this program and measure retention compared with matched controls over 5 years. DESIGN: Longitudinal, matched, case control study and program evaluation. SETTING: Rural communities in Alberta, Canada. PARTICIPANTS: Rural physicians. INTERVENTIONS: Thirty-one rural physicians self-selected their personal skills training program and listed three goals they wished to attain. They were matched by age, specialty, years in practice and size of community with rural physicians who did not participate in a skills training or upgrading program. MAIN OUTCOME MEASURES: Goal attainment for subject physicians, use of skills at 5 years and comparison of rural retention of physicians at 5 years. RESULTS: Thirty-two of thirty-five physicians classified their goal attainment to be as expected or greater, and all were using their new skills at 5 years. Of the matched physicians, 29 training participants remained in rural practice at 5 years compared with only 22 of 29 matched control: relative risk 1.31, confidence interval 1.06-1.62 P < 0.05. CONCLUSIONS: The enrichment program provides focused, valued skills training for rural physicians and long-term benefits to rural 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".