Contextualizing ovarian pain in the late 19th century—Part 1: Women with “hysteria” and “hystero-epilepsy”
Bibliographic record
Abstract
“Hysteria” and “hystero-epilepsy” were common medical diagnoses among physicians during the nineteenth century. In Paris, L’Hôpital de la Salpêtrière—originally a hospice for the poor and a prison for prostitutes and other female inmates—became a center of great interest for the possible role of neurological diseases in these conditions. At the same time in the Americas and Europe, gynecologists were removing women’s ovaries in cases with the same clinical conditions, which emphasized the role of the ovaries in contemporary hysteria studies in France, Great Britain, and the United States. The objective of this article is to explore nineteenth-century conceptualizations of ovarian pain as an organ-pathological substrate for a portion of these diagnoses. The theoretical role of the pelvic organs in these diagnoses has waxed and waned over the centuries, but there have not been many detailed explorations of the associated clinical phenomena. Suggesting an organic basis (le substratum organique) for the diagnoses remains a precarious notion, given the universally repudiated role of the uterus and decreasing interest in the ovary. In contemporary literature, the potential role of the ovary has not been addressed from a detailed medical perspective, however.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".