Ilya Mark Scheinker: Controversial Neuroscientist and Refugee From National Socialist Europe
Bibliographic record
Abstract
Russian-born, Vienna-trained neurologist and neuropathologist Ilya Mark Scheinker collaborated with Josef Gerstmann and Ernst Sträussler in 1936 to describe the familial prion disorder now known as Gerstmann-Sträussler-Scheinker disease. Because of Nazi persecution following the annexation of Austria by Nazi Germany, Scheinker fled from Vienna to Paris, then after the German invasion of France, to New York. With the help of neurologist Tracy Putnam, Scheinker ended up at the University of Cincinnati, although his position was never guaranteed. He more than doubled his prior publications in America, and authored three landmark neuropathology textbooks. Despite his publications, he was denied tenure and had difficulty professionally in the Midwest because of prejudice against his European mannerisms. He moved back to New York for personal reasons in 1952, dying prematurely just 2 years later. Scheinker was twice uprooted, but persevered and eventually found some success as a refugee.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".