Charcot and the psychology of hysteria, with special reference to a never published final case history
Bibliographic record
Abstract
Jean-Martin Charcot is perhaps best remembered for his contributions to organic neurology. However, his pursuit of hysteria, the most prevalent diagnosis in his hospital clinic, yielded no anatomical lesion to account for hysteria’s plethora of somatic disorders assumed due to a purely functional or dynamic lesion in the cerebral cortex. This led Charcot to turn his attention to the psychology of hysteria. Taking advantage of institutional reforms at the Salpêtrière—notably, the establishment of his professorship in nervous diseases—Charcot from the early 1880s focused his teaching increasingly on case histories of hysteria in male as well as female patients. Already renown for his earlier dramatic public lessons on female hysteria, his lessons of the 1880s, of which two volumes were published at the end of the decade, elaborated the issue of psychology in terms of altered states of patient’s suggestibility. By the decade’s end, Charcot’s worldwide reputation rested on the prospects of this work as acknowledged by numerous students, notably medical psychologists Pierre Janet and Sigmund Freud. Yet Charcot’s views remained sketchy. They were discussed at length in his unpublished notes for a lesson intended for May 1893, just a few months before his sudden death. His unpublished notes reveal a detailed case for dreams as illustrating a psychological mechanism underlying hysteria in a 17-year-old Paris artisan. I conclude by considering why this significant climactic case of Charcot’s might have been overlooked by his entourage.
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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 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".