Bibliographic record
Abstract
Until his extradition to Germany in 2005, Ernst Zündel was the largest promoter of Holocaust denial literature in the world. In 1985, Zündel was even put on trial in Toronto for his fallacious publications. The trial was brought by Holocaust survivors seeking to safeguard Holocaust memory, which had grown in Canada's public consciousness during the 1960s and 1970s, but which had been viciously attacked by Zündel. This article explores the origins and history of Zündel's denial, and offers a new perspective on a well-known denier. While antisemitism played an essential role, the author argues that to understand Zündel's denial requires contextualizing his deplorable beliefs, as denial can also serve a special role in deniers' sense of themselves. By taking issues of identity seriously, such as how one fabricates a historical web of meaning, we can better understand what causes some people to deny the undeniable.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.026 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".