The Happy Culture: A Theoretical, Meta-Analytic, and Empirical Review of the Relationship Between Culture and Wealth and Subjective Well-Being
Bibliographic record
Abstract
Do cultural values enhance financial and subjective well-being (SWB)? Taking a multidisciplinary approach, we meta-analytically reviewed the field, found it thinly covered, and focused on individualism. In counter, we collected a broad array of individual-level data, specifically an Internet sample of 8,438 adult respondents. Individual SWB was most strongly associated with cultural values that foster relationships and social capital, which typically accounted for more unique variance in life satisfaction than an individual's salary. At a national level, we used mean-based meta-analysis to construct a comprehensive cultural and SWB database. Results show some reversals from the individual level, particularly masculinity's facet of achievement orientation. In all, the happy nation has low power distance and low uncertainty avoidance, but is high in femininity and individualism, and these effects are interrelated but still partially independent from political and economic institutions. In short, culture matters for individual and national well-being.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".