Turning off the base: Social democracy's neoliberal turn, income inequality, and turnout
Bibliographic record
Abstract
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 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".