Everyday classism in medical school: experiencing marginality and resistance
Bibliographic record
Abstract
OBJECTIVE: To explore the medical school experiences of students who self-identify as coming from a working-class or impoverished family background. METHODS: A questionnaire was administered to Year 3 medical students at a Canadian medical school and in-depth interviews were held with 25 of these students (cohort 1). The same methods were repeated with another Year 3 class 3 years later (cohort 2). RESULTS: While having (or not having) money was the most obvious impact of social class differences, students also discussed more subtle signs of class that made it easier or more difficult to fit in at medical school. Students from working-class or impoverished backgrounds were significantly less likely to report that they fitted in well, and more likely to report that their class background had a negative impact in school. They were also more likely to indicate awareness that a patient's social class may affect their health care treatment. CONCLUSION: Students from working-class or impoverished backgrounds may experience alienation in medical school. Through the commonplace interactions of 'everyday classism' they may experience marginalisation, isolation, disrespect and unintentional slights. At the same time, they suggest that their experiences of exclusion may strengthen their clinical practice.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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 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".