The Early Eugenics Movement and Emerging Professional Psychiatry: Conceptual Transfers and Personal Relationships between Germany and North America, 1880s to 1930s
Bibliographic record
Abstract
French-Austrian psychiatrist Bénédict Augustin Morel's (1809-1873) Traits des dégénérescences physiques, intellectuelles et morales de l'espèce humaine (1857) was fully dedicated to the social problem of "degeneration" and it became very attractive to German-speaking psychiatrists during the latter half of the 19th century. Auguste Forel (1848-1931) and Constantin von Monakow (1853-1930) in Zurich integrated Morel's approach and searched for the somatic and morphological alterations in the human brain; a perspective of research that Ernst Ruedin (1874-1952) at Munich further prolonged into a thorough analysis of hereditary influences on mental health. This paper investigates the continuities and major differences within some early eugenic traditions of the emerging field of psychiatry in the German-speaking countries and North America.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".