Challenging Canada’s Politics of Commemoration Through Sites of (Contested Transnational) Memory
Bibliographic record
Abstract
In this article, I examine public art donation policies and strategies in Toronto, Vancouver, Montreal, and Ottawa1 that seek to provide what these cities consider to be a suitable response to the ever-greater number of demands for commemoration stemming from citizen groups. Some of these demands propose to evince contested or controversial pasts, associated with particular ethno-cultural communities, through traditional lieux de mémoire (sites of memory), such as monuments and memorials. However, the representation of ethno-cultural groups’ pasts (and presents) that fall outside Canada’s imagined and physical national boundaries are perceived by some as a threat to the country’s social cohesion and national unity. Commemoration of people and events that seems as though it might lead to controversy is considered especially challenging. The perception that memorializing ethno-cultural groups’ extra-national narratives might threaten Canadian identity and unity depends on a particular conception of Canada as a multicultural nation that tries to be inclusive but is also necessarily limiting. I argue from the point of ethnography and memory studies that current and proposed public art donation policies and practices informed by this fear circumscribe the ways in which identities and experiences are memorialized in this country. I expose through studying specific controversies surrounding actual and proposed “ethno-cultural monuments”2 how the limits of Canadian multicultural nat
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.062 | 0.055 |
| Scholarly communication | 0.024 | 0.006 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".