The wealth of nations matters: A cross-national analysis of how political orientation and household income affect attitudes toward environmental protection
Bibliographic record
Abstract
The article investigates normative preferences for environmental protection over economic growth registered in 74 countries—based on the European Values Study and the World Value Survey (2017–2022). We employ multi-level logistic regression to demonstrate that Gross Domestic Product per capita moderates the effects of political orientation and household income, both of which tend to be stronger in wealthier countries. Only in wealthy societies are left-leaning and affluent individuals far more likely to prefer environmental protection. Not accounting for moderation leads to underestimating the propensity for political polarization over environmental questions. Hence, our study suggests that large-scale implementation of growth-impeding or wealth-sacrificing environmental policies could face insurmountable public opposition in wealthy societies. Furthermore, failing to account for the moderation by GDP per capita in cross-national studies of environmental attitudes may constitute a confounding factor by aggregating wealthier countries, where the effects of political orientation and household income prove substantial, with the poorer ones, where they appear negligible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".