Following the leader? The impact of federal party leaders on federal elections in Quebec
Bibliographic record
Abstract
The 2011 Canadian Federal Election provided one of the most significant shocks to the Canadian political system, which was the rise of the New Democratic Party in the province of Québec. During this election, NDP party leader Jack Layton showed his connection to Québec throughout the campaign, with his federal political party counterparts showing little to no understanding of Québec. Did this connection give Layton's NDP the advantage?This thesis seeks to understand the impact of political party leaders on vote choice in Québec, primarily through looking at a party leader's geographical, cultural and language connection to Québec. To see if these characteristics of party leaders do have an impact, this thesis created a single variable, called the Québec Score, to see if, holistically, they can contribute to explaining vote choice in Québec. Using aggregate-level data (electoral results at the riding level) for each major political party between 1968 and 2105, this thesis will compare each political party leader's Québec Score to the results in each riding, with controls for incumbent party and personal MP incumbency effects. The results of the thesis shows that there is a connection between these geographical, cultural, and language factors in relation to how successful a political party performs in Québec.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".