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Record W2040045996 · doi:10.1177/0010414004268847

Antipartyism and Third-Party Vote Choice

2004· article· en· W2040045996 on OpenAlexaffabout
Éric Bélanger

Bibliographic record

VenueComparative Political Studies · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPoliticsVotingPolitical scienceFeelingContrast (vision)Single non-transferable votePolitical economyThird partySplit-ticket votingGeneral electionMinor (academic)LawEconomicsSocial psychologyDemocracyPsychology

Abstract

fetched live from OpenAlex

The effect of antiparty sentiment on voting behavior is examined comparatively using recent individual-level electoral survey data from Canada, Britain, and Australia. The author distinguishes two dimensions of antipartyism: the rejection of traditional major-party alternatives (specific antiparty sentiment) and of political parties per se (generalized antiparty sentiment). He argues that disaffected voters in these countries are attracted to third or minor parties and support them to voice antiparty sentiments. The results show that in general, third parties benefit from specific antiparty sentiment at the mass level. The rejection of party politics per se, in contrast, brings citizens to abstain, unless some third parties—antiparty parties such as the Reform Party in Canada and One Nation in Australia—electorally mobilize generalized antiparty feelings. The results also indicate that compulsory voting in Australia affects disaffected voters’ behavior; in particular, those who reject all party alternatives would be more likely to abstain if they had the choice.

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)0.007
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.229
GPT teacher head0.472
Teacher spread0.243 · 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

Citations106
Published2004
Admission routes2
Has abstractyes

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