Genetic and environmental influences on sociopolitical attitudes
Bibliographic record
Abstract
A new paradigm has emerged in which both genetic and environmental factors are cited as possible influences on sociopolitical attitudes. Despite the increasing acceptance of this paradigm, several aspects of the approach remain underdeveloped. Specifically, limitations arise from a reliance on a twins-only design, and all previous studies have used self-reports only. There are also questions about the extent to which existing findings generalize cross-culturally. To address those issues, this study examined individual differences in liberalism/conservatism in a German sample that included twins, their parents, and their spouses and incorporated both self- and peer reports. The self-report findings from this extended twin family design were largely consistent with previous research that used that rater perspective, but they provided higher estimates of heritability, shared parental environmental influences, assortative mating, and genotype-environment correlation than the results from peer reports. The implications of these findings for the measurement and understanding of sociopolitical attitudes are explored.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.019 |
| 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; 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".