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Record W2076979656 · doi:10.1080/14649360701633311

<i>Captain Canuck</i>, audience response, and the project of Canadian nationalism

2007· article· en· W2076979656 on OpenAlexaboutno aff
Jason Dittmer, Soren C. Larsen

Bibliographic record

VenueSocial & Cultural Geography · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsComicsIdentity (music)Audience measurementNationalismMulticulturalismSociologyNational identityConstitutionHumanitiesMedia studiesArt historyArtPolitical scienceLiteratureLawAestheticsPolitics

Abstract

fetched live from OpenAlex

This paper addresses the role of comic books in interpellating national identities, locating the process of national identity formation in the interplay between popular culture producers and their audiences as described by Althusser (Citation1977) and McGee (Citation1975). The empirical section of this paper focuses on Captain Canuck, a Canadian-produced comic book originating in the 1970s and sporadically published through the present day. The authors engaged in a qualitative content analysis of the Captain Canuck comic books, searching for themes and markers of Canadian-ness and looking for audience identifications with those themes and markers in the ‘letter to the editor’ columns published within the comic books themselves. The study finds that through the many incarnations of Captain Canuck various versions of Canadian identity have been projected, with varying degrees of support by the readership. The role of the USA in Canadian identity formation looms large, especially in the positioning of Canadian quality and multiculturalism against the tacitly American lack thereof. Another finding of this research is that there has been a fundamental change in the way Canadian identity is structured as a new, commercially driven Canadiana culture industry has arisen since the 1970s.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.122
Threshold uncertainty score0.515

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0300.027
Scholarly communication0.0110.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations33
Published2007
Admission routes1
Has abstractyes

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