Relaxed Observance of Traditional Marriage Rules Allows Social Connectivity without Loss of Genetic Diversity
Bibliographic record
Abstract
Marriage rules, the community prescriptions that dictate who an individual can or cannot marry, are extremely diverse and universally present in traditional societies. A major focus of research in the early decades of modern anthropology, marriage rules impose social and economic forces that help structure societies and forge connections between them. However, in those early anthropological studies, the biological benefits or disadvantages of marriage rules could not be determined. We revisit this question by applying a novel simulation framework and genome-wide data to explore the effects of Asymmetric Prescriptive Alliance, an elaborate set of marriage rules that has been a focus of research for many anthropologists. Simulations show that strict adherence to these marriage rules reduces genetic diversity on the autosomes, X chromosome and mitochondrial DNA, but relaxed compliance produces genetic diversity similar to random mating. Genome-wide data from the Indonesian community of Rindi, one of the early study populations for Asymmetric Prescriptive Alliance, are more consistent with relaxed compliance than strict adherence. We therefore suggest that, in practice, marriage rules are treated with sufficient flexibility to allow social connectivity without significant degradation of biological diversity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".