Bibliographic record
Abstract
This study examined whether national income can have effects on happiness, or subjective well-being (SWB), over and above those of personal income. To assess the incremental effects of national income on SWB, we conducted cross-sectional multilevel analysis on data from 838,151 individuals in 158 nations. Although greater personal income was consistently related to higher SWB, we found that national income was a boon to life satisfaction but a bane to daily feelings of well-being; individuals in richer nations experienced more worry and anger on average. We also found moderating effects: The income-SWB relationship was stronger at higher levels of national income. This result might be explained by cultural norms, as money is valued more in richer nations. The SWB of more residentially mobile individuals was less affected by national income. Overall, our results suggest that the wealth of the nation one resides in has consequences for one's happiness.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".