Integrating the Health of Socially Vulnerable Populations into Residency Programs
Bibliographic record
Abstract
In Canada, growing disparities in health disproportionally affect socially vulnerable populations. The Royal College of Physician and Surgeons of Canada has attempted to incorporate health equity for socially vulnerable populations within the competency training objectives set forth for internal medicine (IM) residents. However, trainee exposure to these populations beyond inpatient contact in tertiary care hospitals has not traditionally been a requirement of IM training. At the University of Calgary, we have developed a four-week clinical rotation that aims to expose residents to social determinants for socially vulnerable populations. To our knowledge this is the first clinical rotation within an IM program in Canada dedicated to exposing and educating residents on the broader care of socially vulnerable populations. Our goal is to train internists and subspecialists to gain the empathy, skills, and knowledge to better provide care for socially vulnerable populations and to advocate for health equity, throughout their careers.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".