Cross-cultural Evidence of the Relationship between Subjective Well-being and Job Performance: A Meta-analysis
Bibliographic record
Abstract
This meta-analysis examined the differences across countries/regions, and the moderator effects of the study type (cross-sectional vs. longitudinal) on the SWB-job performance relationship. The database consists of 78 independent samples (N = 18,853), located through electronic and manual searches. The results showed that overall SWB (ρ = .37), cognitive SWB (ρ = .27), and affective SWB (ρ = .37) are predictors of job performance. Evidence of cross-cultural effects showed that the magnitude of the SWB-job performance relationship was larger in the Asia-Pacific region than in Europe and the US-Canada region (Asia-Pacific ρ = .41, Europe ρ = .33, USA ρ = .23). Moderator analyses indicated that, on average, cross-sectional (concurrent) and longitudinal (predictive) studies showed similar validity (ρ = .33 vs. ρ = .32). Lastly, we discuss the main contributions, and some practical implications and some limitations of the study are mentioned.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".