Sexual Harassment of Canadian Medical Students: A National Survey
Bibliographic record
Abstract
BACKGROUND: Despite explicit policies and reporting mechanisms in academia designed to prevent harassment and ensure respectful environments, sexual harassment persists. We report on a national survey of Canadian medical students' experiences of sexual harassment perpetrated by faculty, patients and peers, their responses to harassment, and their suggestions for improving the learning environment. METHODS: With ethics approval from all 17 Canadian universities with medical schools, an invitation to participate in an anonymous, electronic survey was included in three Canadian Federation of Medical Students' newsletters (2016). Narrative information about sexual harassment during medical training, perpetrators, ways of coping, sources of support, formal and informal reporting/discussion, and suggestions for change was sought. Three authors then conducted a qualitative analysis and identified emergent themes. FINDINGS: When asked to estimate the number of occurrences of SH experienced during medical school, 188 students reported 807 incidents perpetrated by peers, patients, and, to a lesser extent, faculty. Perpetrators were almost always men and 98% of victims were women. What emerged was a picture of social, educational, and individual conditions under which sexual harassment becomes normalised by faculty, peers and victims. Students often tried to ignore harassment despite finding it confusing, upsetting, and embarrassing. They offered strategies for schools to raise awareness, support students, and prevent or mitigate harms going forward. INTERPRETATION: Sexual harassment is a part of the Canadian medical education environment where most who reported harassment are subject to the dual vulnerabilities of being learners and women. Although survey respondents recognised the systemic nature of the problem, as individuals they often described shame and self-blame when victimised, came up with solutions that implied they were the problem, and often reported thinking silence was less risky than confrontation or official reporting. Many participants believed in the transformative power of education - of themselves and faculty - as a means of improving the medical environment whilst we await social change.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".