Bibliographic record
Abstract
The possibility that national personality traits could explain national subjective well-being (SWB) is controversial, with many researchers arguing that traits are irrelevant to any national-level analysis. The weaknesses of this standpoint are reviewed, followed by a series of empirical investigations. Using Eysenck's 3-factor model (H. J. Eysenck & S. B. G. Eysenck, 1975) and P. T. Costa and R. M. McCrae's (1992b) 5-factor model, the authors found that Neuroticism and Extraversion correlated significantly with national SWB. Lie scale scores were also related strongly to national SWB. Neuroticism and Extraversion incrementally predicted SWB above gross national product per capita. The strength of these results indicates that personality can have stronger relationships at national levels of analysis than at the individual level. National personality traits appear to be unwisely neglected, having considerable but largely unconsidered explanatory power.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".