The Mass Murder of the European Jews and the Concept of ‘Genocide’ in the Nuremberg Trials: Reassessing Raphaël Lemkin’s Impact
Bibliographic record
Abstract
Nuremberg’s prosecutors prominently used Lemkin’s genocide concept. They also dealt in detail with the mass murder of Europe’s Jews. However, for them ‘genocide’ and the Holocaust were not congruent. They used different definitions of Lemkin’s concept and interpreted the relationship between the mass murder of the European Jews and the entire mass violence of the Nazis differently. Lemkin had little influence on the application of his concept in the Nuremberg trials between 1945 and 1949. The implementation of the 1948 United Nations Genocide Convention put an end to the broad use of the original concept from 1944. Although both Lemkin and the prosecutors in the Nuremberg trials went through a similar development in the early post-war years to underline the special character of the Nazi mass murder of the European Jews. The development paths were different, but led to a similar result.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".