Does Turnout Decline Matter? Electoral Turnout and Partisan Choice in the 1997 Canadian Federal Election
Bibliographic record
Abstract
Abstract.The recent decline in electoral turnout in Canada has attracted the concern of scholars and public officials, but the partisan consequences of this decline have received only scant attention. We begin to address that question with a simulation based on the 1997 Canadian Election Study. Based on estimated probabilities of individual behaviour derived from multinomial logit models of voter choice, we find that higher turnout would have likely hurt the Liberal party in Quebec, but slightly helped the Liberals outside of Quebec. We interpret this pattern as evidence that generational politics plays a role in shaping the relationship between electoral turnout and partisan support. Résumé.Le déclin récent dans la participation électorale au Canada a attiré l'intérêt des chercheurs et des représentants de l'Etat, mais les conséquences partisanes de ce déclin n'ont sucité qu'une attention limitée. Nous commençons à aborder cette question à l'aide d'une simulation basée sur l'Etude électorale canadienne de 1997. En nous appuyant sur des probabilités estimatives du comportement individuel dérivées de modèles logistique multinominal du choix d'électeur, nous constatons qu'une participation plus importante aurait probablement nuit au Parti Libéral au Québec, mais aurait légèrement favorisé le Parti Libéral en dehors du Québec. Nous interprétons ce modèle comme preuve que la politique de générations contribue à la formation du rapport entre la participation électorale et l'appui partisan.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".