Neuroscience in Nazi Europe Part II: Resistance against the Third Reich
Bibliographic record
Abstract
Previously, I mentioned that not all neuroscientists collaborated with the Nazis, who from 1933 to 1945 tried to eliminate neurologic and psychiatric disease from the gene pool. Oskar and Cécile Vogt openly resisted and courageously protested against the Nazi regime and its policies, and have been discussed previously in the neurology literature. Here I discuss Alexander Mitscherlich, Haakon Saethre, Walther Spielmeyer, Jules Tinel, and Johannes Pompe. Other neuroscientists had ambivalent roles, including Hans Creutzfeldt, who has been discussed previously. Here, I discuss Max Nonne, Karl Bonhoeffer, and Oswald Bumke. The neuroscientists who resisted had different backgrounds and motivations that likely influenced their behavior, but this group undoubtedly saved lives of colleagues, friends, and patients, or at least prevented forced sterilizations. By recognizing and understanding the actions of these heroes of neuroscience, we pay homage and realize how ethics and morals do not need to be compromised even in dark times.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".