Evaluating distributed medical education: what are the community’s expectations?
Bibliographic record
Abstract
OBJECTIVES: This study aimed to explore community members' perceptions of present and future impacts of the implementation of an undergraduate medical education programme in an underserved community. METHODS: We conducted semi-structured interviews with eight key informants representing the health, education, business, economy, media and political sectors. A two-stage approach was used. In the first stage, the interviews were analysed to identify sector-specific impacts informants perceived as already occurring or which they hoped to see in the future. The transcripts were then re-analysed to determine any underlying themes that crossed sectors. RESULTS: Community leaders described impacts that were already occurring in all sectors and also described changes in the community itself. Four underlying themes emerged: an increase in pride and status; partnership development; community self-efficacy, and community development. These underlying themes appear to characterise the development of social capital in the community. CONCLUSIONS: The implementation of distributed undergraduate medical education programmes in rural and underserved communities may impact their host communities in ways other than the production of a rural doctor workforce. Further studies to quantify impacts in diverse sectors and to explore possible links with social capital are needed.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".