Rebecca Cook, interview, Toronto, Canada, 2022
Bibliographic record
Abstract
Rebecca Cook, University of Toronto, Toronto, Ontario, Canada, 2022 November 3 and 11, oral history interview, by Lillie Guo, Los Angeles, California, USA. The inteview was conducted over the Internet (Zoom) as part of the Health and Human Rights Oral History Project. Rebecca Cook, A.B., M.A., M.P.A., J.D., J.S.D., is a Professor Emerita in the Faculty of Law, the Faculty of Medicine and the Joint Centre for Bioethics at the University of Toronto, and Co-Director, International Reproductive and Sexual Health Law Program, University of Toronto. A pioneering and prolific scholar in the field of international women's rights, she is a Member of the Order of Canada, a Fellow of the Royal Society of Canada, the recipient of the Certificate of Recognition for Outstanding Contribution to Women’s Health by the International Federation of Gynecology and Obstetrics (FIGO), and is the Ethical and Legal Issues Co-editor of the International Journal of Gynecology and Obstetrics. She has served on many boards and advisory panels, including the Center for Reproductive Rights, Ford Foundation, the Guttmacher Institute, International Women's Rights Action Watch, IPAS, Pathfinder International and the World Health Organization. In her oral history, Cook recounts her years of work at the nexus of women’s health and human rights, including her formational research and work linking abortion, contraception, maternal mortality, and other reproductive health issues to the international human rights framework. She charts the evolution of the reproductive health field from its biomedical origins to a rights-based enterprise addressing the accountability of state and non-state actors for violations of women’s rights. She details specific cases and norms that were turning points for the field, from her early years at the International Planned Parenthood Federation through her professorships at Columbia University and the University of Toronto.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.209 | 0.035 |
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".