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Record W4415228723 · doi:10.4324/9781003366911-26

Canadian Superheroes and the Struggle for National Representation

2025· book-chapter· en· W4415228723 on OpenAlexaboutno aff
Anthony Enns

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsNarrativeNational identityPopularityOpposition (politics)Representation (politics)Dominance (genetics)Symbol (formal)

Abstract

fetched live from OpenAlex

As historians often note, the success of the comic book industry in North America was indelibly linked to the rise of superheroes; yet it was virtually impossible for Canadian comic books to compete with US imports, so early superheroes were almost exclusively American. This situation changed briefly during WWII, when a ban on imports allowed Canadian artists to develop their own national superheroes, like Johnny Canuck; yet the ban was lifted soon after the war, and the nation was once again flooded with American comics. It wasn’t until the 1970s and 1980s that Canadian publishers began to introduce new Canadian superheroes, like Captain Canuck and Northguard, in a period that became known as the “Silver Age” of Canadian comics. The enduring popularity of these characters shows that there is still a desire on the part of many readers to consume superhero narratives featuring Canadian characters, and these narratives often frame Canadian identity in opposition or relation to American identity due to the economic dominance of American publishers and the close connection between the superhero genre and American popular culture. This chapter examines the history of Canadian superheroes, and it particularly focuses on how this history reflects an ongoing struggle to imagine an appropriate symbol of Canadian identity, which has proven to be extremely difficult within a marketplace dominated by American companies and characters.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.806
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.034
GPT teacher head0.239
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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