Local Economies, Local Policy Impacts and Federal Electoral Behaviour in Canada
Bibliographic record
Abstract
The fortunes of local, regional and provincial economies have often been linked to geographical variation in electoral outcomes, and nowhere more so than in Canada. This article examines economic localism in Canadian voting behaviour by estimating a model of voters' decisions in the 1993 and 1997 federal elections. Individual-specific determinants of the vote measured in the Canadian Election Study are supplemented by measures of voters' local economies and of the local impacts of policy changes. Voters punish the federal government for bad times in their locale and for policy changes that hurt the local economy. This effect is independent of what voters think about their own finances and about the provincial and national economies. The electoral impact of the local economy does not depend on whether government is acknowledged as a potent economic actor, or on the voter's level of political information. However, the relevance of the local economy for national-level electoral behaviour can be "primed" by campaign events, just like any other criterion of voting choice. The response to local economic conditions is part of a broader explanation for geographic patterns of electoral support in Canada.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".