Women in surgery: The social construction of gender in surgical practice
Bibliographic record
Abstract
INTRODUCTION: Despite comprising over half of Canadian medical graduates, women remain underrepresented within surgery. Strategies to address this gap have largely focused on increasing numbers or targeting individual women, overlooking subtle, systemic gender inequities that may deter women from the field. METHODS: 67 h of participant observation with six surgeons and semi-structured interviews with six women surgeons were conducted at a Canadian academic hospital to explore how gendered processes shape surgical life. Data was analyzed iteratively and thematically. RESULTS: Gender influenced women surgeons' lives across three levels: organizationally, their surgical status was questioned and undermined; individually, they navigated a double bind of being both a woman and a surgeon; and environmentally, their bodies conflicted with cultural and physical norms of surgical spaces. CONCLUSION: This study suggests that gender inequities are deeply ingrained in surgical structures and practices, highlighting the need for systemic transformations to ensure women are fully included and valued within surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.025 | 0.047 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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 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".