Mnemonic naturalism: Anti-communist memory politics and multiculturalism in Canada
Bibliographic record
Abstract
Since the fall of the Berlin Wall, debates on how to remember the communist past have gained prominence, focusing on symbolic, moral, and mnemonic capitals. Aligning with an “international current” of anti-communist commemoration, Canada’s Memorial to the Victims of Communism extends these debates to a country with no history of state-led communism. Using frameworks in cultural sociology and memory studies, this article analyzes the Memorial to the Victims of Communism’s “living” digital archive to examine its socio-political work. Our findings reveal that—unlike in Europe, where mnemonic capital often rewrites national narratives—the Memorial to the Victims of Communism redistributes mnemonic capital along cultural lines and reinforces Canadian national identity through disputes over name, design, and location. While Conservatives sought to embed anti-communism into Canadian identity, the Liberal iteration universalizes victimhood through an aestheticized logic we call mnemonic naturalism. This memorial reflects broader tensions in Canadian multiculturalism, consolidating symbolic capital while erasing historical complexity and diverse immigrant experiences.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.045 | 0.022 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".