Women in Medicine: The Limits of Individualism in Academic Medicine
Bibliographic record
Abstract
In the 21st century, more than ever before, issues facing women in medicine, such as pay equity and workplace harassment, are being explored and attended to by physicians and health care institutions. Discussions about women in medicine almost exclusively center around women physicians, even though most women in medicine are, in fact, not physicians. In addition, these discussions typically focus on gender, often failing to consider how race, class, and other dimensions of identity influence the experiences of women in medicine. In this article, the authors argue that neoliberal feminism is the dominant strand of feminism in the discourse of women in medicine. With its focus on the individual and a conception of success defined in largely economic terms, neoliberal feminism fails to consider the broader conditions in which women are situated and, therefore, limits structural criticism and the possibility for all women to engage in social justice. The authors suggest that the pandemic is an opportunity to pursue a more expansive vision of feminism in medicine. They propose intersectional feminism as a theoretical framework that can widen the understanding of what is possible: moving from individual actions resulting in incremental change to collective action that can transform systems. Intersectional feminism enables a push for structures, institutions, and practices that support all workers, including basic income, labor protections, public childcare, accessible health care, transportation justice, and migrant rights. In so doing, intersectional feminism calls for solidarity with and among women both within and outside of medicine.
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 | 0.037 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.146 |
| Scholarly communication | 0.027 | 0.015 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".