Sites of similarity, sites of difference: constructing Canada in the graphic narrative
Bibliographic record
Abstract
Canadian superhero comic books represent a politically significant opportunity to study popular conceptions of national politics, cultures, and identities. Canadian superheroes are 'others' in the shadow their American neighbours, but embrace this 'Not-American otherness' as a central factor defining Canadian national identity. The diversity of Canadian multiculturalism collapses into a monolithic white/male/Anglophone identity produced in the tensions created by the binary relmionship between 'self-as-other' and 'American' articulated by the texts, creating one universalised and naturalised "Canadian" identity. This thesis seeks to politicise existing surveys that ignore the political implications of the comic book texts, and to critique other problematic methodologies in the comics discourse: tendencies towards canon-building, and resistance to interdisciplinary methodologies. I forward a social/cultural/political analysis that draws equally on my multiple backgrounds and subject positions as a university-educated art historian, a popular culture critic, a Canadian, and a (feminist) reader and fan of superhero comic books.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.022 | 0.062 |
| Scholarly communication | 0.023 | 0.015 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".