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Record W3198595948 · doi:10.1017/s0043887121000149

The Generational and Institutional Sources of the Global Decline in Voter Turnout

2021· article· en· W3198595948 on OpenAlexaffabout
Filip Kostelka, André Blais

Bibliographic record

VenueWorld Politics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsTurnoutDemocracyVoter turnoutVotingPolitical scienceGlobalizationCompetition (biology)InequalityDemographic economicsPolitical economyEconomicsPolitics

Abstract

fetched live from OpenAlex

ABSTRACT Why has voter turnout declined in democracies all over the world? This article draws on findings from microlevel studies and theorizes two explanations: generational change and a rise in the number of elective institutions. The empirical section tests these hypotheses along with other explanations proposed in the literature—shifts in party/candidate competition, voting-age reform, weakening group mobilization, income inequality, and economic globalization. The authors conduct two analyses. The first analysis employs an original data set covering all post-1945 democratic national elections. The second studies individual-level data from the Comparative Study of Electoral Systems and British, Canadian, and US national election studies. The results strongly support the generational change and elective institutions hypotheses, which account for most of the decline in voter turnout. These findings have important implications for a better understanding of the current transformations of representative democracy and the challenges it faces.

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)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.335
Teacher spread0.306 · 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

Citations114
Published2021
Admission routes2
Has abstractyes

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