Why Do Conservatives Report Being Happier Than Liberals? The Contribution of Neuroticism
Bibliographic record
Abstract
Previous studies suggest that conservatives in the United States are happier than liberals. This difference has been attributed to factors including differences in socioeconomic status, group memberships, and system-justifying beliefs. We suggest that differences between liberals and conservatives in personality traits may provide an additional account for the "happiness gap". Specifically, we investigated the role of neuroticism (or conversely, emotional stability) in explaining the conservative-liberal happiness gap. In Study 1 (N = 619), we assessed the correlation between political orientation (PO) and satisfaction with life (SWL), controlling for the Big Five traits, religiosity, income, and demographic variables. Neuroticism, conscientiousness, and religiosity each accounted for the PO-SWL correlation. In Study 2 (N = 700), neuroticism, system justification beliefs, conscientiousness, and income each accounted for PO-SWL correlation. In both studies, neuroticism negatively correlated with conservatism. We suggest that individual differences in neuroticism represent a previously under-examined contributor to the SWL disparity between conservatives and liberals.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".