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Record W4285351450 · doi:10.1080/02722011.2021.1986557

COVID-19 in Canada through the Eyes of Right-Wing Intellectuals

2021· article· en· W4285351450 on OpenAlexafffundabout
Timothy van den Brink, Frédéric Boily

Bibliographic record

VenueThe American Review of Canadian Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsRoyal Military College Saint-JeanSimon Fraser UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNationalismIdeologySovereigntyPoliticsProtectionismConvergence (economics)Political scienceLocalismSociologyPolitical economyGlobalizationLawEconomic growthInternational tradeEconomics

Abstract

fetched live from OpenAlex

Political ideologies shape our societies, and those on the right in Canada remain understudied. As ideologies continue to evolve, we are left blind to greater distance or perhaps convergence between the right in Quebec and the rest of Canada. The COVID-19 pandemic is an excellent opportunity to compare the work of prominent intellectuals while they have uniform subject matter. As such, this research analyses the output of nine columnists from the National Post, Journal de Montréal, and Calgary Herald from March 13 to May 1, 2020. Our analysis focused on the depictions of political actors, and the themes of nationalism and globalization. There is convergence between the right in Quebec and the rest of Canada in the critiques of Prime Minister Justin Trudeau and anti-globalist positions. However, discussions of sovereignty endure in Quebec, built upon cultural protectionism. The right in English Canada largely supported Canadian nationalism and economic protectionism.

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)0.009
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.148
Threshold uncertainty score0.988

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0230.026
Scholarly communication0.0200.005
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.061
GPT teacher head0.369
Teacher spread0.308 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

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