Bibliographic record
Abstract
In 1984, Judith Walzer Leavitt edited a volume entitled Women and Health in America: Historical Readings (Madison, Wisconsin, University of Wisconsin Press, 1984), an outstanding collection of articles exploring the history of women in medicine. Now, finally, a quarter of a century later, another equally impressive collection of essays has been published, this one edited by Ellen S. More, Elizabeth Fee, and Manon Parry. Leavitt's volume, which included essays on a broad range of issues related to women's health and health careers, proved to be a mainstay for courses on the history of medicine and gender studies, and medicine in America. This book focuses more narrowly on women physicians, but its essays are equally impressive, and it, too, should become a staple in many courses. The essays include contributions by female historians and one male historian that were initially presented at a symposium hosted by the National Library of Medicine, entitled “Women Physicians, Women's Politics, and Women's Health: Emerging Narratives.”
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.047 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".