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Record W2902051391 · doi:10.1017/pls.2018.17

Genetic and environmental influences on sociopolitical attitudes

2018· article· en· W2902051391 on OpenAlexaff
Edward Bell, Christian Kandler, Rainer Riemann

Bibliographic record

VenuePolitics and the Life Sciences · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsConservatismPerspective (graphical)Assortative matingTwin studyHeritabilityGermanPsychologySocial psychologySample (material)Behavioural geneticsMatingDevelopmental psychologyPolitical scienceGeographyEcologyPoliticsBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.019
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.352
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2018
Admission routes1
Has abstractyes

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