Slave Trade and Colonial Expansion Resulted in Strong Sex-Biased Admixture in South Africa
Bibliographic record
Abstract
Abstract The colonial-period arrival of Europeans in southern Africa is associated with strong sex-biased migration by which male settlers displaced indigenous Khoekhoe and San men. Simultaneously, the importation of South Asian, Indonesian and Eastern African slaves may have contributed female-biased migration to Cape Town and surrounding areas. We examine the spatial and temporal spread of sex-biased migration from the Cape northward into Namaqualand and the southern Kalahari using genetic data from more than 1,400 individuals. In all regions, admixture patterns were sex-biased, with evidence of a greater male contribution of European ancestry and greater female contribution of Khoe-San ancestry. While admixture among Khoe-San, European, equatorial African, and Asian groups has likely been continuous from the founding of Cape Town to present-day, we find that Khoe-San groups further north experienced a single pulse of European admixture 6-8 generations ago. European admixture was followed by additional Khoe-San gene flow, potentially reflecting an aggregation of indigenous groups due to disruption by colonial interlopers. Male migration into the northern frontier territories was not a homogenous group of expanding Afrikaners and slaves. The Nama show evidence of distinct founder effects and derive 15% of their male lineages from Asian men, a pattern absent in the ≠Khomani San. Khoe-San ancestry from the paternal line is greatly diminished in populations from Cape Town, the Cederberg Mountains and Upington, but remains more frequent in self-identified ethnically indigenous groups. Strikingly, we estimate that Khoe-San Y-chromosomes were experiencing unprecedented population growth at the time of European arrival. Our findings shed light on the patterns of admixture and the population history of South Africa as the colonial frontier expanded.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".