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Record W2346091695 · doi:10.3138/ctr.166.005

When Canada Goes Viral: The Canada Party and the Circulation of Political Satire

2016· article· en· W2346091695 on OpenAlexvenueaboutno aff
Kimberley McLeod

Bibliographic record

VenueCanadian Theatre Review · 2016
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAppropriationPoliticsPresidential systemDemocracyIronyCitizen journalismPolitical sciencePresidential electionMedia studiesLawArtSociologyLiterature

Abstract

fetched live from OpenAlex

In September 2012, a satirical video declaring Canada as a candidate for the American presidential election went viral. Created by Brian Calvert and Chris Cannon, the “The Canada Party—Meet the Canada Party” video was part of a prank in which the two proposed that Canada would be a better presidential option than either Barack Obama or a Republican Party candidate. The prank is part of a recent performance trend that scholar L. M. Bogad names “electoral guerrilla theatre.” This type of performance responds to the limitations of democratic electoral systems via the appropriation of signs and parodying of electoral norms. Responses to this prank revealed some of the challenges activist performers face when dealing with mass media, which can shift the message of tactical interventions and misread irony. Major international news outlets assumed the prank was primarily about stereotypical, nationalistic differences between Canada and the US. Though this particular video did feature some national stereotypes, the artists developed a scathing critique of Canadian policies with the Canada Party campaign. Their work revealed how freely news media, political culture, and satire now circulate across borders.

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 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 score0.982
Threshold uncertainty score0.651

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)0.0010.000

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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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.

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
Published2016
Admission routes2
Has abstractyes

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