A Party that Went Viral? The Drivers of Support for the Parti Conservateur du Québec in the 2022 Election
Bibliographic record
Abstract
Abstract Even though the Parti Conservateur du Québec (PCQ) did not manage to elect any members to the Assemblée nationale in Quebec's 2022 general election, this political party nonetheless received nearly 13 per cent of the popular vote. The party mainly campaigned on issues related to the economic right, but also discontent with the Legault government's COVID-19 health measures. We assess the extent to which these different drivers of support explain vote choice in favour of the PCQ using individual-level survey data from the 2022 Quebec Election Study. We find that the PCQ did succeed in gathering support on the basis of these issues, but that it was also able to attract voters with a lesser appetite for climate change mitigation as well as a populist and cynical outlook on politics. The party also appears to be especially popular among younger, male and less educated voters living outside the Greater Montreal region.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".