Confronting the "Good Death": Nazi Euthanasia on Trial, 1945-1953, Michael S. Bryant (Boulder: University Press of Colorado, 2005), x + 267 pp., $34.95.
Bibliographic record
Abstract
In his important new book, Michael Bryant makes it depressingly clear that after the immediate postwar period, bringing Nazi perpetrators to justice was not a priority for either the United States or West Germany. His study chronicles the initially sincere attempt by the US and later the West Germans to prosecute participants in the “T-4” euthanasia program (code-named by the Nazis after the program's office address in Berlin at Tiergartenstrasse 4), as well as the rapid degeneration of these trials. Bryant's is the most comprehensive and nuanced analysis of these trials to date; he outlines not only the history of the trials, but also the legal issues surrounding the prosecution of euthanasia crimes, the history of euthanasia in Germany, and the T-4 program's relationship to the “Final Solution” during the Second World War. Bryant links these interrelated questions seamlessly, drawing for the reader a clear picture of the contingencies that led eventually to the “spectacular failure” of the euthanasia trials.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".