Bibliographic record
Abstract
Sri Lanka’s rich palaeoanthropological and archaeological record as well as the present demographic aspects have much to offer in aiding our understanding of the island’s ancient past and recent population structure. Sri Lanka has yielded skeletal evidence for the earliest anatomically modern humans from South Asia indicating very early settlement of the region. Following early hunter-gatherer dispersals over 50,000 years ago, agricultural populations expanded to the region with historic settlements and urbanisation creating complex societies in the last three millennia. Through circum-Indian Ocean trade networks in historic times and colonial expansion in the last 500 years, population diversification has continued with groups of multiple genetic and ethno-linguistic backgrounds arriving and settling in the island. These early and later migrants share a gene pool that connects them to descendants of today, who form Sri Lanka’s multi-ethnic, multicultural, and multi-religious society. Using an anthropological perspective, this article investigates how complex societal and biological diversity would have developed over time in island Lanka. An appreciation of deep time, beyond historic records, helps us recognize that human evolution and diversification has been shaped over thousands of years, while an evidence-based, scientific approach is proposed to eliminate flawed ethnocentric interpretations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".