Genetic Foundations of Attitude Formation
Bibliographic record
Abstract
Abstract Since the pioneering work of Eaves and Eysenck (1974) appeared in Nature some 40 years ago, psychologists, sociologists, political scientists, and behavioral geneticists have investigated the effects of nature and nurture on the formation of social attitudes. It has consistently been found that manifestations of social attitudes (i.e., preferences, values, and beliefs pertaining to things such as politics, religion and the treatment of ingroups and outgroups) are genetically influenced. More recently, researchers have focused their efforts on the psychophysiological pathways between gene activity and attitudes. In particular, a broad body of research examines how personality traits may be a link between genetic factors and political orientations. The latter are typically treated as either a single left–right dimension or divided into two core aspects: resistance to change/authoritarian conservatism and acceptance of inequality/social dominance orientation . In this essay, we provide an overview of this research, present some findings from our recent international behavioral genetic study on the topic, and identify key issues for future research. We suggest that future studies treat attitude formation as a complex process in which genetic factors and the psychophysiological phenomena that stem from them are affected by the surrounding social environment and culture. Such research will require (i) international study designs capturing individual and cultural levels of variation and (ii) interdisciplinary collaboration among scientists and researchers in various fields of study such as genetics, psychology, sociology, political science, neuroscience, and human biology.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".