Subjective Well-Being Around the World: Trends and Predictors Across the Life Span
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using representative cross-sections from 166 nations (more than 1.7 million respondents), we examined differences in three measures of subjective well-being over the life span. Globally, and in the individual regions of the world, we found only very small differences in life satisfaction and negative affect. By contrast, decreases in positive affect were larger. We then examined four important predictors of subjective well-being and how their associations changed: marriage, employment, prosociality, and life meaning. These predictors were typically associated with higher subjective well-being over the life span in every world region. Marriage showed only very small associations for the three outcomes, whereas employment had larger effects that peaked around age 50 years. Prosociality had practically significant associations only with positive affect, and life meaning had strong, consistent associations with all subjective-well-being measures across regions and ages. These findings enhance our understanding of subjective-well-being patterns and what matters for subjective well-being across the life span.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it