10 International Evidence on the Social Context of Well-Being
Bibliographic record
Abstract
Abstract This chapter uses the first three waves of the Gallup World Poll to investigate differences across countries, cultures, and regions in the factors linked to life satisfaction, paying special attention to the social context. The principal findings are: First, using the larger pooled sample, the chapter finds that answers to the satisfaction with life and Cantril ladder questions provide consistent views of what constitutes a good life, with an average of the two measures providing a clearer picture than either measure on its own. Second, this chapter finds strong evidence for the importance of both income and social context variables in explaining within-country and international differences in well-being. For most specifications tested, the combined effects of a few measures of the social and institutional context are as large as those of income in explaining both international and intra-national differences in life satisfaction. Third, the very significant influences of both income and social factors permit the calculation of compensating differentials for social factors. We find very large income-equivalent values for key measures of the social context. Fourth, the international similarity of the estimated equations suggests that the large international differences in average life evaluations are not due to different approaches to the meaning of a good life, but to differing social, institutional, and economic life circumstances.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.262 | 0.011 |
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".