The Waffen-SS Man in the Gallery: The Yaroslav Hunka Scandal and Canada’s Undigested Past
Bibliographic record
Abstract
Abstract: In September 2023, in the Canadian House of Commons, the Speaker of the House introduced the Ukrainian president, Volodymyr Zelensky, to a 98 year old Ukrainian Waffen-SS veteran named Yaroslav Hunka, who was introduced as a “Canadian and Ukrainian hero” and given two standing ovations from the floor. This incident developed into an international political scandal and resulted in the resignation of the Speaker of the House. The scandal re-opened the painful subject of Canada’s legacy of allowing thousands of Nazi collaborators into the country. This article evaluates this controversy within the context of normative Canadian multiculturalism, which has stimulated and facilitated a multi-generational cult of Waffen-SS veneration in the Ukrainian Canadian community. Its powerful lobby has mobilized significant resources to prevent access to key sources that would allow for a candid engagement with this difficult past. In November 2024, the Canadian government reaffirmed its denial of access to crucial archival collections pertaining to war criminals living in Canada. However, in 2025, scholars uncovered the Deschênes Commission’s list of 776 alleged war criminals, released in an access to information and privacy request in 2019. This discovery—in combination with work in archives in countries with more archival transparency, such as the United States, Israel, Ukraine, and Lithuania—has now provided an opportunity for independent, critical analysis of Canada’s treatment of alleged war criminals.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.075 | 0.021 |
| Scholarly communication | 0.017 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".