Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines in-depth the recent argument popularized by Brazilian gynecologist, Elsimar Coutinho and colleagues, that regular menstruation in is an unhealthy and unnecessary process that causes women countless health and emotional problems, and that the most medically advanced treatment for menstruation would be its total cessation in all women of reproductive age. The author explores the long history of medical views of menstruation which are often informed by the notion that menstruation is an ailment, or a disorder that requires a medical intervention. The author compares this view with the most recent research on menstruation by evolutionary biologists, such as Margie Profet, and anthropologists Emily Martin and Beverly Strassman, who have, in their own ways, found a variety of health benefits linked to menstruation other than the established link between fertility and the menses. Underlying the author's review of the medical pronouncement on women's natural cycles is the question: Why do women menstruate? Her conclusion indicates that this question has not been adequately addressed in medical and scientific literature, which has sought to explain away or eradicate menstruation. New research needs to assess the value of the regular processes of women's bodies so that can we fully understand their role and function in the physical and emotional health of all women.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 it