Ancient Human DNA and African Population History
Bibliographic record
Abstract
Abstract Ancient DNA has emerged as a powerful tool for investigating the human past and reconstructing the movements, mixtures, and adaptations that have structured genetic variation throughout human history. While the study of genome-wide ancient human DNA was initially restricted to regions with temperate climates, methodological breakthroughs have now extended the reach of ancient DNA analysis to parts of the world with hot and humid climates that are less conducive to biomolecular preservation. This includes Africa, where people harbor more genetic diversity than can be found anywhere else on the planet, reflecting deep and complex population histories. Since the first ancient African genome was published in 2015, the number of individuals with genome-wide data has increased to nearly 200, with greater coverage of diverse geographical, temporal, and cultural contexts. Ancient DNA sequences have revealed genetic variation in ancient African foragers that no longer exists in unadmixed form; illuminated how local-, regional-, and continental-scale demographic processes associated with the spread of food production and new technologies changed genetic landscapes; and discerned notable variation in interactions among people with distinct genetic ancestries, cultural practices, and, likely, languages. Despite an increasing number of studies focused on African ancient DNA, multiple regions and time periods have yet to be explored. Research to date has primarily focused on the past several thousand years in eastern and southern Africa, setting up northern, western, and central Africa, as well as deeper time periods, as key areas for future investigation. As ancient DNA research becomes increasingly integrated with anthropology and archaeology, it is advantageous to understand the basic methodological and analytical techniques, the types of questions that can be investigated, and the ways in which the discipline may continue to grow and evolve. Critically, the growth and evolution of ancient DNA research must include attention to the ethics of this work, both in African contexts and globally. In particular, it is essential that research is conducted in a way that minimizes the potential of harm to both the living and the dead. Scientists conducting ancient DNA research in Africa especially must also contend with structural challenges, including a lack of ancient DNA facilities on the continent, the extensive fragmentation of African heritage (including ancient human remains) among curating institutions worldwide, and the complexities of identifying descendant groups and other stakeholders in the wake of colonial and postcolonial disruptions and displacements. Ancient DNA research projects should be designed in a way that contributes to capacity building and the reduction of inequities between the Global North and South to ensure that the research benefits the people and communities with connections to the ancient individuals studied. While ensuring that future studies are rooted in ethical and equitable practices will require considerable collective action, ancient DNA research has already become an integral part of our understanding of African population history and will continue to shape our understanding of the African past.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".