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Record W2241607383 · doi:10.1017/cbo9780511790980.009

Turnout

2004· book-chapter· en· W2241607383 on OpenAlexaboutno aff
Pippa Norris

Bibliographic record

VenueCambridge University Press eBooks · 2004
Typebook-chapter
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsTurnoutLegislaturePolitical scienceVotingPopulationPolitical economyBallotDemographic economicsModernization theoryPoliticsDevelopment economicsGeographyDemographySociologyEconomicsLaw

Abstract

fetched live from OpenAlex

In many established democracies, concern about eroding participation at the ballot box has been expressed widely, with commentators suggesting that we are seeing the “vanishing voter,” especially in America. Yet patterns of voting turnout in the United States are far from typical and, indeed, always have been during the postwar era. Levels of electoral participation today vary dramatically among democracies. In the countries under comparison, on average more than 80% of the voting age population (VAP) turned out in legislative elections held during the 1990s in Iceland, Israel, and Sweden, compared with less than half of the equivalent group in the United States and Switzerland (see Figure 7.1). The comparison shows that turnout cannot simply be explained by differences in the historical experiences of older and newer democracies, as the Czech Republic, Chile, and South Korea all rank in the top third of the comparison, whereas the United States, Canada, and Japan lag near the bottom. Worldwide there are even greater disparities, with more than 90% of the voting age population (Vote/VAP) participating in legislative elections during the last decade in Malta, Uruguay, and Indonesia, compared with less than a third in Mali, Colombia, and Senegal. To explain these patterns, the first part of this chapter considers accounts based on rational-choice institutionalism and the cultural modernization theories. The second part examines the evidence and analyzes the extent to which turnout varies by political institutions, by electoral laws, and by voting procedures, as well as by the social characteristics and cultural attitudes of voters, and by levels of societal modernization.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.109
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1090.034

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 head0.045
GPT teacher head0.265
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2004
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooks→Same topicElectoral Systems and Political Participation→French-language works237,207→