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Record W3157038430 · doi:10.29173/psur224

On Guard: The Discourse of Difference in Trudeau’s Speech on National Unity

2021· article· en· W3157038430 on OpenAlexvenueaboutno aff
Francis Rweyongeza

Bibliographic record

VenuePolitical Science Undergraduate Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsParliamentExceptionalismNational identityMulticulturalismMedia studiesColonialismBattleCitizenshipLawPolitical scienceIndigenousState (computer science)SociologyPoliticsHistory

Abstract

fetched live from OpenAlex

Prime Minister Justin Trudeau’s July 1, 2017 speech to commemorate 150 years of Canadian Confederation and its seemingly banal content and delivery ironically beckons for critical attention. Delivered to the Prince of Wales on Parliament Hill and millions via television and Internet, the address capped off the immense cultural spectacle of Canada’s sesquicentennial with tributes to Canadian exceptionalism in battle and in sport. However, behind references to reconciliation and tolerance is a well-documented history of contestation that runs contrary to the international myth of Canadian unity. This essay deconstructs a consonance of perspectives on Indigenous relations, multiculturalism, and citizenship proposed by Prime Minister Trudeau in his Canada 150 address on Parliament Hill that is inconsistent with a defining decade of Canadian resistance. I analyze the speech’s attempts to whitewash Canada’s colonial origins and dispel numerous claims of peaceful coexistence between the nation-state and various minorities, fundamentally challenging perceptions of Canadian identity and national values.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.088
Threshold uncertainty score0.563

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0130.020
Scholarly communication0.0090.004
Open science0.0020.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.359
Teacher spread0.317 · 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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