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Record W3199849072 · doi:10.3138/jcs-2019-0041

Ambiguously Hip: The Tragically Hip and Canadian Nationalism

2021· article· en· W3199849072 on OpenAlexvenueaboutno aff
Gregory Millard

Bibliographic record

VenueJournal of Canadian Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismAppropriationContext (archaeology)SociologyNational identityAestheticsIdentity (music)Gender studiesHistoryPoliticsLawPolitical scienceArtPhilosophyEpistemologyArchaeology

Abstract

fetched live from OpenAlex

The Tragically Hip are a remarkable, indeed unique, phenomenon in Canadian popular music. Their 2016 final tour, undertaken after lead singer Gordon Downie was diagnosed with brain cancer, spectacularly reinforced longstanding perceptions of a privileged link between the band’s music and Canadian national identity. This article probes this connection, asking why deeply ambiguous and often critical references to Canada sufficed to raise The Hip to an extraordinary status as icons of Canadian nationalism. Drawing from theories of “banal” and “everyday” nationalism, it argues that, while The Hip’s work may legitimately be read as nationalist, Canada’s position as a culturally peripheral nation is the key to explaining the incongruous appropriation of the Hip’s work for nationalist self-celebration. The discourse around The Tragically Hip, then, helps to illuminate some of the ways in which nationalism works in a culturally peripheral context.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0350.037
Scholarly communication0.0110.003
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.063
GPT teacher head0.228
Teacher spread0.165 · 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 designNot applicable
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

Citations0
Published2021
Admission routes2
Has abstractyes

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