Rural versus Urban General Internal Medicine – What Factors are Influencing Resident’s Choice of Practice?
Bibliographic record
Abstract
Objective: To understand the factors influencing General Internal Medicine (GIM) fellows to choose a rural versus urban clinical practice. Methods: A descriptive study employing individual interviews of GIM fellows was conducted. Questions probed fellows’ choice of practice, perceived characteristics of practice location, definition of rural medicine, awareness of incentives for rural practice, and suggestions on attracting GIM specialists to rural areas. Results: 12 GIM fellows were interviewed. Regarding the choice of practice location, nearly all participants mentioned that their decision was influenced by where they were raised or where their family was currently located. The diversity of rural practice was described as an attracting feature. Lifestyle factors were also important in their choice of practice. Conclusion: Factors associated with rural practice amongst GIM fellows include (1) relationship to region, (2) characteristics of practice, and (3) lifestyle preferences. Recruitment strategies leveraging these factors would assist in drawing physicians to rural areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".