Consanguineous marriage and its genetic outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Marriage has long been the predominant institution within which procreation occurs and genes are transmitted. Therefore a key initial step in the investigation of genetic differences at individual and population levels is to examine past and present marriage preferences in different societies. In terms of populations genetics theory, infinite population size and random mating are important preconditions of the Hardy-Weinberg principle, which describes the intergenerational transmission of genes. It is, however, doubtful whether either of these assumptions has ever existed in human populations. For example, estimates of the effective population size of the Out-of-Africa migration some 60,000-70,000 years ago (Behar et al., 2008) range from approximately 10,000 (Harpending et al., 1998) to as few as 700 individuals (Zhivotovsky et al., 2003). Further, since the early human groups were itinerant hunter-gatherers, random mating would have been impossible and close kin mating almost inevitable. \n \nEven in countries with large immigrant communities, such as the United States, Canada, and Australia, recent arrivals typically marry within their own ethnic and/or religious communities during the first and second post migration generations. This practice, described as positive assortative mating, provides strong social advantages. However, it has important genetic implications, since it is probable that couples from the same national, ethnic, or religious sub-community will have a significant proportion of their genes in common. Therefore, as will be further discussed, their progeny are more likely to be homozygous (or, more correctly, autozygous) for a detrimental recessive disorder (Bittles, 2002). \n \nThe probability of genetic drift, i.e. chance fluctuations in gene frequencies in successive generations, is greatest in communities with restricted numbers of potential mating couples. In human populations this situation can arise in a variety of ways; e.g., through founder effect, when a subgroup of a population establishes a new breeding colony; via a demographic bottleneck following a major disease- or disaster-related mortality (Auton et al., 2009); and in populations subdivided into multiple, strictly endomagous communities (Bittles, 2009a). \n \nVirtually all traditional human societies are divided into long-established communities, with limited intercommunity marriage (Bittles, 2008), and genome based association studies in industrialized Western societies have demonstrated the on-going existence of similar, if less pronounced, subdivisions leading to significant population stratification (McEvoy et al., 2009). A higher probability of homozygosity results, with a consequent increased likelihood of recessive gene expression. Since a recessive founder or de novo mutation can rapidly increase in frequency within a small community by chance alone, the birth of an affected child may occur whether the parents are known to be consanguineous or consider themselves nonrelatives (Zlotogora et al., 2006).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it