Imagining the Exceptional Canada: Nation, Art, and Social Change in Canada’s Charitable Sector
Bibliographic record
Abstract
This article draws on a case study of the Michaëlle Jean Foundation—a Canadian arts-based charitable organization—to examine processes of national imagining in a charitable sector shaped by neo-liberal capitalism. Utilizing interviews, field notes, and organizational documents, I show how discourses of the nation intersect with the arts to reframe political struggles along culturalist lines, such that social justice optics mask an apolitical and technical model for addressing structural injustice. While foundation-funded artists can engage in creative pushback, I argue that the neo-liberalization of the sector severely limits this national (re)imagining, either shutting it down completely or reconfiguring it in line with a depoliticized framework for social change, further reaffirming dominant mythologies of Canada. With this case-focused analysis, I hope to illuminate how the censorship of resistance in the charitable sector is not always an explicit process driven by the threat of funding withdrawal. Rather, a much more insidious form of depoliticization can occur within charitable sector contexts that have institutionalized and continue to circulate dominant discourses of the nation in their imaginings of better futures—in this instance, through intersections with the arts.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.067 | 0.050 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".