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Record W4415914914 · doi:10.1017/s147567652510039x

Power and ideology – A comparison of citizens’ and politicians’ satisfaction with democracy

2025· article· en· W4415914914 on OpenAlexafffund
Benjamin Ferland, Valere Gaspard, Johan Savoy

Bibliographic record

VenueEuropean Journal of Political Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDemocracyIdeologyScholarshipPower (physics)PoliticsPublic opinion

Abstract

fetched live from OpenAlex

Abstract The scholarship on satisfaction with democracy has increased significantly in recent decades, with scholars investigating how democratic satisfaction influences political attitudes and behaviors as well as the individual and contextual determinants of citizens ’ satisfaction with democracy. To our knowledge, however, scholars omitted to examine the democratic satisfaction of politicians . Making use of survey data from the Comparative Candidates Survey, this research note addresses this gap in the literature. As a first step in this endeavor, we pose two objectives. First, we want to compare levels of democratic satisfaction across citizens and politicians in different countries to evaluate whether mass-elite gaps are apparent. Second, we want to replicate core findings from the research on citizens but with politicians. As such, we examine two hallmark findings in the literature on democratic satisfaction with respect to the role of ideological extremism/nicheness and the winner-loser gap at elections. Our study contributes to the growing literature on elites’ attitudes and behaviors and identifies some of the conditions that favor and undermine politicians’ satisfaction with democracy. This is a crucial research endeavor given elites’ influence on public opinion and democratic stability.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.093
GPT teacher head0.467
Teacher spread0.373 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

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