Political party affiliation, political ideology and mortality
Bibliographic record
Abstract
BACKGROUND: Ecological and cross-sectional studies have indicated that conservative political ideology is associated with better health. Longitudinal analyses of mortality are needed because subjective assessments of ideology may confound subjective assessments of health, particularly in cross-sectional analyses. METHODS: Data were derived from the 2008 General Social Survey-National Death Index data set. Cox proportional analysis models were used to determine whether political party affiliation or political ideology was associated with time to death. Also, we attempted to identify whether self-reported happiness and self-rated health acted as mediators between political beliefs and time to death. RESULTS: In this analysis of 32,830 participants and a total follow-up time of 498,845 person-years, we find that political party affiliation and political ideology are associated with mortality. However, with the exception of independents (adjusted HR (AHR)=0.93, 95% CI 0.90 to 0.97), political party differences are explained by the participants' underlying sociodemographic characteristics. With respect to ideology, conservatives (AHR=1.06, 95% CI 1.01 to 1.12) and moderates (AHR=1.06, 95% CI 1.01 to 1.11) are at greater risk for mortality during follow-up than liberals. CONCLUSIONS: Political party affiliation and political ideology appear to be different predictors of mortality.
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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 | 0.039 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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; 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".