How Social Class Shapes Attitudes on Economic Inequality: The Competing Forces of Self-Interest and Legitimation
Bibliographic record
Abstract
Abstract: Using survey data from the World Values Survey (WVS) and national-level statistics from various official sources, we explore how attitudes toward economic inequality are shaped by economic conditions across 24 Organization for Economic Cooperation and Development (OECD). Consistent with the economic self-interest thesis, we find that where income inequality is low, those in lower economic positions tend to be less likely than those in higher economic positions to favor it being increased. On the other hand, where economic resources are highly unequally distributed, the adverse effects of inequality climb the class ladder, resulting in the middle classes being just as likely as the working class to favor a reduction in inequality. Our results further suggest that people tend to see current levels of inequality as legitimate, regardless of their own economic position, but nonetheless desire economic change—i.e., they would like to see inequality reduced—if they perceive it could improve their own economic situation.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".