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Record W4376142282 · doi:10.1017/s000842392300015x

Pandemic Populism: Explaining Support for the People's Party of Canada in the 2021 Federal Election

2023· article· en· W4376142282 on OpenAlex
Mike Medeiros, Timothy B. Gravelle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Political Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsWilfrid Laurier University
FundersWilfrid Laurier University
KeywordsOpposition (politics)PopulismPandemicPolitical sciencePrimary electionEliteCoronavirus disease 2019 (COVID-19)Public healthPolitical economyGeneral electionPublic administrationPoliticsSociologyLawMedicine

Abstract

fetched live from OpenAlex

Abstract The COVID-19 pandemic has seen opponents of public health mandates deploy a range of populist and anti-elite arguments. The 2021 Canadian federal election was an exceptional “pandemic election” in which the COVID-19 health crisis took centre stage. But the election campaign also saw the populist People's Party of Canada (PPC) rise to prominence by opposing pandemic-related public health restrictions. While the party failed to win a seat, it did manage to triple its vote share (1.6 per cent to 4.9 per cent). It is unclear, however, what factors led to the rise in support for the PPC. To explore this issue, we draw on an original post-election survey ( n = 18,950) and focus on populist attitudes and opposition to COVID-19-related public health restrictions. Results from regression models and structural equation models (SEMs) indicate that opposition to public health restrictions was a much stronger factor than populism in shaping support for the PPC.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.324
Teacher spread0.287 · 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