A Right‐Wing Populist Turn in the Conservative Party of Canada? Continuities and Ruptures Under the Leadership of Pierre Poilievre (2022–2025)
Bibliographic record
Abstract
Since his election as leader of the Conservative Party of Canada (CPC) in 2022, Pierre Poilievre has been associated with populism in media and political discourse, with implicit and explicit comparisons to Donald Trump. This article investigates the validity of such assessments by applying "complex" theories of populism, which conceptualize populism as an interplay of ideology, communication style, and organizational strategy. Drawing on a qualitative content analysis from the 2022-2025 period, we examine the extent to which Poilievre adopts populist repertoires or reflects continuity with Canadian conservatism. The findings suggest an uneven picture: while his core ideological and policy positions remain largely rooted in Harper-era neoliberalism and law-and-order priorities, Poilievre's communication style-marked by anti-elite rhetoric, heightened depictions of societal crisis, and combative messaging-reflects a discernible populist turn. Organizationally, Poilievre maintains CPC structures but seeks to reshape them through stricter party discipline, outsider narratives, and unmediated digital outreach strategies that antagonize traditional media. Beyond the Canadian case, the article contributes to theoretical debates by operationalizing a multidimensional framework for the analysis of contemporary populist politics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.020 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".