Quebec's new political equilibrium: the interaction of three ideological axes
Bibliographic record
Abstract
As little attention has been given to ideological voting in Quebec, this thesis fills the gap by assessing the extent of ideological voting in the province and by identifying the relevant ideologies in Quebec. Building on a contemporary conception of ideology, three ideological axes are studied: the question nationale, interventionism and outgroups. Through multinomial logistic regression, it is confirmed that both the question nationale and the outgroup ideological axes have individual significant effect on vote choice in Quebec. The introduction of a triple interaction between all ideological axes also results in a more comprehensive portrait of ideological voting in the province. The likelihood of Quebecers voting for some parties is strengthened when they hold specific bundles of ideological preferences based on the three identified ideological axes. The results indicate that voters will neglect their interventionists ideological preferences to avoid conflict and vote for the CAQ or the PLQ, potentially due to a lack of political parties representing all ideological bundles. Conversely, PQ and QS voters do not oversee any axes as all matter in their decisional process. This thesis highlights the importance of analyzing interaction effects in the study of ideology in order to paint a full portrait of ideological voting in complex ideological frameworks
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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.
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".