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Record W2138795396 · doi:10.1017/s0008423901777918

Canadian Exceptionalism: Explaining Differences over Time in Provincial and Federal Voter Turnout

2001· article· en· W2138795396 on OpenAlexaboutno aff
Donley T. Studlar

Bibliographic record

VenueCanadian Journal of Political Science · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsTurnoutVoter turnoutPolitical scienceDemographic economicsExceptionalismPopulationPoliticsGeographyDemographyPublic administrationVotingEconomicsSociologyLaw

Abstract

fetched live from OpenAlex

Canada is unusual among advanced industrial democracies in having some provinces which regularly have greater voter turnouts for provincial than for federal elections. Provincial and federal turnouts by province in Canada are analyzed for the 1945-1998 period using multiple regression analysis, both for each set of elections and by comparing differences between the two. Federal turnout has declined over the years but provincial turnout appears to have increased slightly. Although the effects found here largely confirm previous findings about the relative effects of different types of variables found for the Canadian federal level only, several of the political explanations previously supported in cross-national research find less support. Instead, region, population density, months since the last federal or provincial election, and season of the year generally have greater and sometimes more consistent effects. This suggests the need for more studies of turnout in democracies at sub-central levels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.029
GPT teacher head0.311
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2001
Admission routes1
Has abstractyes

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