A contextualised review of genomic evidence for gene flow events between Papuans and Indigenous Australians in Cape York, Queensland
Bibliographic record
Abstract
It has long been accepted that the Indigenous groups of Australia's Cape York Peninsula have numerous cultural traits that were adopted from people in New Guinea and/or the Torres Strait Islands after the formation of the Torres Strait around 8,000 years ago.However, opinions differ on whether the movement of the traits in question was accompanied by gene flow events.Some argue for a significant amount of gene flow resulting from voyages from New Guinea and the Torres Strait Islands down the east coast of Cape York.Others contend that there was only contact at the northern end of the Cape and that the cultural traits spread through down-the-line transmission.In recent years partnerships between Australian institutions and Indigenous communities in Cape York have led to new genetic research that provides benefits to both parties.We review the currently available genetic data that have the potential to shed light on this issue, concluding that the data are inconsistent with significant gene flow between Indigenous Australians and Papuan people between 8,000 years ago and the colonial period.There are indications of gene flow, but it most likely occurred in the Pleistocene rather than the Holocene.As such, the currently available genomic data do not support the hypothesis that the diffusion of cultural traits from New Guinea and/or the Torres Strait Islands into Cape York was accompanied by gene flow.The data suggest instead that the cultural traits most probably spread via down-the-line trade, exchange, and imitation.Our review highlights the gaps in the available genomic information from contemporary and ancestral descendants of Australia's first settlers, and we suggest that researchers adopt a more collaborative approach, involving Indigenous communities and their knowledge in project design, data collection, and dissemination, in future genomic studies in Australia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".