Does the Presence of a Minority Government Affect the Robustness of Economic Voting? the Case of Canada in 2006
Bibliographic record
Abstract
While empirical analysis suggests that economic voting is broadly applicable across industrialized democracies, most of those studies have focused on the United States and Western Europe. Canada has received relatively less attention in economic voting studies and when it has, the resulting evidence has been somewhat ambiguous. Canada offers a fascinating opportunity to examine whether the presence of a minority government affects the robustness of economic voting especially given that in 2006 Canadians replaced a minority Liberal government with a minority Conservative one. While most analyses of this election have focused on the role of successive scandals for contributing to the Liberals defeat, little work has explicitly examined the role of economic factors in explaining the election's outcome. Thus, studying the 2006 Canadian federal election allows for both an examination of the importance of economics in Canadian electoral outcomes and voters' attribution of responsibility for the economy under minority government. In this paper, we test our central hypothesis that Canadians do engage in economic voting using public opinion data collected as part of the Canadian Election Survey (CES). We find that while Canadians did engage in retrospective sociotropic economic voting in 2006, prospective economic evaluations did not affect vote choice among the Canadian electorate.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".