Personal Life Satisfaction as a Measure of Societal Happiness is an Individualistic Presumption: Evidence from Fifty Countries
Bibliographic record
Abstract
Abstract Numerous studies document that societal happiness is correlated with individualism, but the nature of this phenomenon remains understudied. In the current paper, we address this gap and test the reasoning that individualism correlates with societal happiness because the most common measure of societal happiness (i.e., country-level aggregates of personal life satisfaction) is individualism-themed. With the data collected from 13,009 participants across fifty countries, we compare associations of four types of happiness (out of which three are more collectivism-themed than personal life satisfaction) with two different measures of individualism. We replicated previous findings by demonstrating that societal happiness measured as country-level aggregate of personal life satisfaction is correlated with individualism. Importantly though, we also found that the country-level aggregates of the collectivism-themed measures of happiness do not tend to be significantly correlated with individualism. Implications for happiness studies and for policy makers are signaled.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".