Genetic effects on migration behavior contribute to increasing spatial differentiation at trait-associated loci in Estonia
Bibliographic record
Abstract
Emerging evidence suggests that migration behavior can be selective with respect to individuals' genotypes, producing genotype-environment correlations that standard methods used in genetic association studies cannot correct. We investigate this phenomenon by examining the spatial dynamics of polygenic scores (PGSs) in Estonia. Our analyses show that contemporary migrations intensify inter-regional differences in PGSs for multiple traits, with educational attainment (EA) PGS showing the strongest effect and largely explaining the inter-regional variation of other PGSs. This differentiation is mainly driven by individuals with higher EA PGS migrating to Estonia's two largest cities from the rest of the country. Importantly, this pattern replicates within families: individuals migrating to the major cities have, on average, higher EA PGS than their siblings staying elsewhere. This trend has persisted since the mid-20th century, despite significant societal changes. These findings illustrate how migration shapes genetic differentiation within a population and highlight direct genetic effects influencing this process.
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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 | 0.000 | 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 | 0.000 |
| 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".