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Record W4405398058 · doi:10.1111/1475-6765.12750

Are poor people poorly heard?

2024· article· en· W4405398058 on OpenAlexfundaboutno aff
Julie Sevenans, Awenig Marié, Christian Breunig, Stefaan Walgrave, Karolin Soontjens, Rens Vliegenthart

Bibliographic record

VenueEuropean Journal of Political Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaVlaamse regeringFonds Wetenschappelijk OnderzoekUniversität KonstanzUniversity of TorontoFonds De La Recherche Scientifique - FNRSSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsInequalityPerceptionRepresentation (politics)Political scienceDemographic economicsSociologyEconomicsPoliticsPsychologyLaw

Abstract

fetched live from OpenAlex

Abstract A growing body of literature shows that the preferences of poorer groups in society are less well represented than the preferences of the rich. This paper scrutinises one possible explanation of inequality in representation: that politicians hold biased perceptions of what citizens want. We conducted surveys with citizens and politicians in four countries: Belgium, Switzerland, Canada and Germany. Citizens provided their preferences regarding concrete policy proposals, and then politicians estimated these preferences. Comparing politicians’ estimates with the actual preferences of different social groups, the paper shows that politicians’ perceptions are closer to the preferences of the richer than to those of poorer people for issues that matter most for economic inequality: socio‐economic issues. Further, we find that especially right‐wing politicians tend to think about the preferences of richer societal groups when estimating the preferences of their partisan electorates on socio‐economic matters.

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)0.010
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.226
GPT teacher head0.496
Teacher spread0.269 · 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.

Study designTheoretical or conceptual
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

Citations5
Published2024
Admission routes2
Has abstractyes

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