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Record W4387610122 · doi:10.1017/s0007123423000364

When Do Citizens Consider Political Parties Legitimate?

2023· article· en· W4387610122 on OpenAlexfundno aff
Ann‐Kristin Kölln

Bibliographic record

VenueBritish Journal of Political Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
FundersYork UniversityGöteborgs UniversitetUniversität WienUniversity of CambridgeUniversität Trier
KeywordsPoliticsPolitical scienceLaw and economicsPolitical economyLawEconomics

Abstract

fetched live from OpenAlex

Abstract Research on negative partisanship and affective polarization shows that wholesale rejections of individual parties are a common and growing phenomenon. This article offers a novel perspective on assessments of parties by considering citizens' legitimacy perceptions of political parties as institutional players. Combining research on political parties and public opinion, I develop a theoretical framework that explains how parties' characteristics shape their perception as legitimate institutional players. I argue that governing experience, age, ideology, and democratic behaviour provide informational cues to citizens about how democratically dangerous a party is. To test my argument, I fielded a cross-sectional survey in seven West European countries and a large-scale survey experiment. The results consistently show that citizens use party-level cues such as ideological moderation and democratic behaviour to form party legitimacy perceptions. The findings have important public opinion implications for political parties and their institutional role in democracies.

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)0.003
metaresearch head score (Gemma)0.015
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.067
GPT teacher head0.379
Teacher spread0.312 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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