The Beginnings of Scientific Psychiatric Twin Research: Luxenburger’s 1928 “Preliminary Report on the Psychiatric Examination of a Series of Twins”
Bibliographic record
Abstract
While reports of twin pairs concordant for insanity began to appear in the 19th century, the first modern psychiatric twin study that fulfilled Galton's 1875 promise of the value of the twin method was published by the German Psychiatrist and Geneticist Hans Luxenburger in 1928. Luxenburger introduced four major methodological advances: the use of representative sampling, proband-wise concordance, rigorous zygosity diagnoses, and age correction. He used a narrow Kraepelinian diagnostic approach diagnosis and ascertained twins hospitalized, on a specific day, in all large Bavarian asylums. We include a brief biography of Luxenburger, summarize the findings of his paper and provide a full English translation in the appendix. Luxenburger presents evidence that the frequency of twinning in those with severe mental illness were as expected and reports proband-wise concordance for probable and definite dementia praecox (MZ-76%, DZ-0%) and manic-depressive insanity (MZ-75%, DZ-0%). He also examined eccentricity and hyperthymic or hypothymic personality in the dementia praecox and manic-depressive pairs, respectively. Luxenburger's substantial contributions to the history of psychiatric genetics should be considered in the context of his intimate but ambivalent relationship with the racial-hygiene policy of the German National Socialists.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.040 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.003 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".