‘When Ovaries Retire’: Contrasting Women’s Experiences with Feminist and Medical Models of Menopause
Bibliographic record
Abstract
Western biomedical paradigms tend to treat health as the absence of disease and the appropriate functioning of biologic and psychophysiologic processes in the individual. Non-biomedical or lay concepts of health often focus on ability to function, or on social or spiritual well-being evidenced by physical fitness, energy, vitality, absence of pain, feeling healthy and the ability to maintain social relationships (Calnan, 1987). Differences between biomedical and lay concepts of health and illness are most pronounced when symptoms are amorphous and ambiguous. Scholarly works on menopausal syndrome traditionally treat the symptoms profile as nonspecific and psychological or psychosomatic (Kaufert, 1982), thus suggesting that there will be little agreement in lay discussions of the experience of menopause. Support group discussions suggest exactly the reverse. Members demonstrate remarkable consistency and agreement in their notions of symptom clusters, cause, and relief, but symptom profiles frequently are presented in highly subjective terms more in keeping with folk medical under-standings of health and illness. This article hopes to demonstrate the importance of using self-help groups to understand experientially constructed notions of health and illness and to argue for greater biomedical attention to lay understandings of menopausal syndrome.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".