Théodore Simon (1873-1961). Itinéraire d’un psychiatre engagé pour la professionnalisation des infirmiers et infirmières d’asile
Bibliographic record
Abstract
Well-known for having created the famous Metric Scale of Intelligence along with the psychologist Alfred Binet (1857-1911), what is less known is that Théodore Simon (1873-1961) was also a major actor of the professionalization of psychiatric nurses in France. From his engaged textbook published in 1911 to his journal, explicitly titled ?L'Infirmier Psychiatrique,? which he created in 1953 via the specialized school he founded and directed between 1946 and 1957 at the Maison Blanche hospital in Neuilly-sur-Marne, Simon worked throughout his career for the acknowledgment and the training of those he considered as true partners. This is what we want to demonstrate in this paper, which redraws the forgotten career history of this militant psychiatrist in order to shine a light on his commitment to the professionalization of psychiatric nurses.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".