Bibliographic record
Abstract
Authors provide a much-needed analysis of the dynamic decades after 1945, when both Canada and the United States began using federal funds to expand health-care access, and biomedical research and authority reached new heights. Focusing on a wide range of issues - including childbirth, abortion and sterilization, palliative care, pharmaceutical regulation, immigration, and Native health care - these essays illuminate the ironic promise of biomedicine, postwar transformations in reproduction, the varied work and belief-systems of female health-care providers, and national differences in women's health activism. Contributors include Aline Charles (Laval University), Barbara Clow (independent scholar), Laura E. Ettinger (Clarkson University), Georgina Feldberg (York University), Karen Flynn (York University), Vanessa Northington Gamble (Association of American Medical Colleges), Elena R. Gutiérrez (University of Illinois, Chicago), Molly Ladd-Taylor (York University), Alison Li (independent scholar), Maureen McCall (physician, Nepal), Michelle L. McClellan (University of Georgia), Kathryn McPherson (York University), Dawn Dorothy Nickel (University of Alberta), Heather Munro Prescott (Central Connecticut State University), Leslie J. Reagan (University of Illinois, Urbana-Champaign), Susan M. Reverby (Wellesley College), Susan L. Smith (University of Alberta), Ann Starr (visual artist and writer), and Judith Bender Zelmanovits (York University).
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".