MétaCan
Menu
Back to cohort
Record W4386000578 · doi:10.1111/polp.12550

Turning off the base: Social democracy's neoliberal turn, income inequality, and turnout

2023· article· en· W4386000578 on OpenAlexaff
Matthew Polacko

Bibliographic record

VenuePolitics &amp Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsTurnoutEconomic inequalityVotingDemocracyPresidential systemPoliticsInequalityWelfare stateEconomicsPolitical sciencePolarization (electrochemistry)Political economyDemographic economicsLaw

Abstract

fetched live from OpenAlex

Abstract Greater party system polarization has recently been shown to influence voter turnout under conditions of higher income inequality. This article builds on these findings by introducing into the framework the policy positions of social democratic parties. It does so through multilevel regression on a sample of 30 advanced democracies in 111 elections, from 1996 to 2019. In doing so, it contributes to the identification of party policy offerings as a mechanism moderating inequality and turnout. It finds that income inequality significantly reduces voter turnout, which is substantially magnified when social democratic parties adopt rightward welfare state positions. It also finds that social democratic parties can largely mitigate the negative effects of inequality on turnout for low‐income individuals by offering leftist welfare state positions. The findings carry important implications for understanding the electoral consequences of both party positioning and rising inequality in advanced democracies. Related Articles Simon, Christopher A., and Raymond Tatalovich. 2022. “The Turnout Myth and Referendum Voting in the United States.” Politics & Policy 50(3): 472–86. https://doi.org/10.1111/polp.12483 . Stockemer, Daniel, and Stephanie Parent. 2013. “The Inequality Turnout Nexus: New Evidence from Presidential Elections.” Politics & Policy 42(2): 221–45. https://doi.org/10.1111/polp.12067 . Wilford, Allan M. 2020. “Understanding the Competing Effects of Economic Hardship and Income Inequality on Voter Turnout.” Politics & Policy 48(2): 314–38. https://doi.org/10.1111/polp.12344 .

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.073
GPT teacher head0.400
Teacher spread0.327 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePolitics &amp PolicySame topicElectoral Systems and Political ParticipationFrench-language works237,207