Unsettling Canadian Heritage: Decolonial Aesthetics in Canadian Video and Performance Art
Bibliographic record
Abstract
Issues of settler colonialism in Canada are prominent in public discourse in the wake of the 2015 findings by the Truth and Reconciliation Commission. These histories, rooted in legacies of cultural genocide and trauma, disrupt national mythologies of the Canadian state as benevolent and inclusive. Grappling with this moment of reconciliation—and the resistance and resentment entangled in this process—we suggest contemporary artists are leading the way in critically examining these dynamics. In this article we investigate decolonialism as an aesthetic strategy. Focusing on how decolonial aesthetics engages with the discourse of Canadian heritage, we examine the work of contemporary artists Leah Decter, Jacqueline Hoàng Nguyễn, and Caroline Monnet. These artists, all working with archives, communities, and histories located geographically or conceptually at the peripheries of Canada, employ diverse media to engage with heritage objects, concepts, and events, to question settler colonialism in the public realm. Through our analysis of their work, we argue for the ways in which their projects unsettle dominant national histories. We contend that Decter’s, Hoàng Nguyễn’s, and Monnet’s decolonial aesthetics mobilize heritage to unpack the complexities of the Canadian state.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.028 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".