The Role of German Academic Medicine and Science in the Medical Crimes of the Third Reich and the Shoah: The Continuing Legacy
Bibliographic record
Abstract
Despite the revelations of the Nuremberg Medical Trial and subsequent prosecutions, the reality is that with particular respect to medicine and the role of leading academic and scientific institutions during the so-called "Third Reich," the postwar period war was marked by a "Great Silence." With few exceptions, this silence continued until the 1980's, when increasing systematic scholarly research and inadvertent discoveries revealed the significant role played by the German and Austrian medical profession during the Nazi period and the Shoah. The discoveries included body parts of victims of Nazi terror in the collections of university institutes of anatomy and scientific research. The Pernkopf Atlas of Human Anatomy represents a legacy from Nazi medicine. Although it includes images from Nazi victims, its accuracy makes it a valued resource in surgery. The Vienna Protocol is a new halachic responsum on the question of what to do with newly discovered remains from Nazi victims and their data, and can provide guidance in the ethical reasoning on whether to use the Pernkopf atlas.
 Photo credit: Faculty of Medicine of the University of Vienna under it's newly appointed dean, Prof. Eduard Pernkopf, immediately after the annexation of Austria into Nazi Germany that occurred in March 1938. Used with permission of the Österreichische Nationalbibliothek (Austrian National Library, Vienna, Austria).
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.043 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".