Neuroticism and State Differences in Partisanship in the USA: Emotional Stability, Ideological Orientation, and Republican Preference
Bibliographic record
Abstract
Relations between Neuroticism, Republican-Democrat preference, and conservative-liberal ideological orientation were examined with the states of the USA as units of analysis. State-aggregated Neuroticism scores were based on 1999-2005 responses of 619,397 residents to the 44-item Big Five Inventory. State Republican-Democrat preference was based on the 2002 occupancy of the U.S. Presidency, U.S. House, U.S. Senate, state House, state Senate, and state Governorship, as well as state-aggregated partisanship responses of 110,305 persons to 1998-2002 CBS/New York Times national polls. State conservative-liberal ideological orientation was based on 1998-2002 state-aggregated responses of 103,828 persons to CBS/New York Times national polls. Using correlation, partial correlation, and hierarchical multiple regression, it was determined that lower state resident Neuroticism is associated with Republican preference, and that both conservative-liberal ideological orientation and state resident Neuroticism account independently for variance in Republican-Democrat preference. These relations were found when 1998-2002 state socioeconomic status, white percent, and urban percent were statistically considered and controlled in partial correlation and hierarchical regression analysis. In contrast, corresponding analyses involving the other Big Five showed that only Openness and Conscientiousness showed any relation to partisanship, albeit infrequent and inconsistent. State resident Neuroticism is the primary state-level Big Five predictor of Republican/Democratic Party choice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".