Exploring the Socialization Experiences of Medical Students From Social Science and Humanities Backgrounds
Bibliographic record
Abstract
PURPOSE: To explore the structural, cultural, and interpersonal issues that may contribute to the inadvertent marginalization of medical students with social science and humanities (SSH) backgrounds. METHOD: Using the hidden curriculum as an analytic construct, the lead author interviewed 14 medical students with SSH backgrounds at the University of Toronto Faculty of Medicine from February to October 2015. The authors analyzed the interview transcripts for common themes around positive and negative cultural, structural, and interpersonal dimensions of the socialization process. RESULTS: Participants reported barriers to applying to medical school: needing to complete prerequisite courses and to do well on an exam geared toward those with a strong science background (the Medical College Admission Test) and lacking an application cohort. Some participants felt they were not ideal candidates for medical school. Participants appreciated how their SSH backgrounds and associated skill sets shaped both their perspectives on patient care and their developing professional identities. However, they perceived that others largely deemed their previous training as irrelevant, and they felt marginalized in medical school by peers, instructors, and the curriculum. These experiences led both to self-censorship, which enabled them to seem to conform to normative behaviors, and to the pursuit of reaffirming elective experiences. CONCLUSIONS: The existing hidden curriculum inadvertently marginalizes SSH medical students; their experiences likely reflect the socialization experiences of other students from underrepresented backgrounds. Curricular and institutional reforms are imperative to shift the hidden curriculum toward one of epistemological inclusion that better supports students from nontraditional backgrounds.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".