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Record W4362666768 · doi:10.1080/13501763.2023.2177323

Who got what they wanted? Investigating the role of institutional agenda setting, costly policies, and status quo bias as explanations to income based unequal responsiveness

2023· article· en· W4362666768 on OpenAlexfundno aff
Mikael Persson

Bibliographic record

VenueJournal of European Public Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdUniversité de GenèveGöteborgs UniversitetMcGill UniversityVetenskapsrådetAmerican Political Science Association
KeywordsStatus quoStatus quo biasPoliticsPublic economicsPolitical scienceEconomicsPolitical economyPublic administrationLaw

Abstract

fetched live from OpenAlex

Previous research has shown that elected officials are more responsive to the opinions of high-income citizens than to those of middle and working-class citizens in the United States. This is often explained by the fact that economic elites make campaign contributions to political elites, leading to decision-making that aligns with the preferences of the affluent. This paper examines the opinion-policy link in Swedish politics, where campaign contributions are relatively low. Despite this, the study finds that high-income citizens still receive the most policy responsiveness. Three alternative possible explanations are discussed. Do high-income citizens receive more responsiveness because (a) they are better able to put issues on the political agenda, (b) because they are easier to satisfy and prefer ‘cheaper’ symbolic policy reforms, while low-income citizens prefer more costly policies or (c) because the status quo bias works to the advantage of high-income citizens?

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)0.004
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.866
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.101
GPT teacher head0.378
Teacher spread0.277 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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