Canada, Still the Exception? Populist Communication Styles Among Canadian Federal Leaders on X (Twitter)
Bibliographic record
Abstract
Abstract This study assesses the validity and reliability of empirical strategies derived from the study of European populisms by applying them to the case of Canada. Using a dataset of 5,845 original tweets by Canadian federal party leaders in 2022, we compare the prevalence and intensity of three characteristic populist discourses: “people-centrism,” “anti-elitism” and “exclusion of others.” Our results raise questions about the role of party ideology in shaping populist communication styles, by revealing a convergence among opposition leaders around primarily economic representations of the “people” and political portrayals of the “elite.” We also confirm the hunch that Canada is “exceptional” with respect to the prevalence of “exclusion of others,” demonstrating that this discourse is rare and has not been embraced by mainstream politics. Finally, the study adds to the skepticism about the value of “people-centrism” to operationalizing populism, given the widespread nature of this discourse.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".