Homo erectus technological behaviors during the Middle Pleistocene Transition: Engaji Nanyori, Oldupai Gorge
Bibliographic record
Abstract
Abstract The Acheulean technocomplex is a milestone in the evolutionary adaptability, technological development, and dispersal of Homo erectus . While the earlier phases of the Acheulean have been thoroughly investigated in Eastern Africa, reliably dated assemblages in environmental context spanning the Middle Pleistocene Transition (1.2–0.8 Ma) are extremely rare at a global scale. Engaji Nanyori (Bed III, Oldupai Gorge) is one of a few sites offering a window into Acheulean behavior during this critical period of climatic crisis and aridification. We study lithic assemblages from recent excavations of an Acheulean occupational sequence dated 1.1–0.9 Ma, revealing a stable technological system that focused on flake production by relying on Oldowan-like knapping strategies while rendering infrequent the manufacture of Large Cutting Tools. We present a continental analysis of Acheulean technologies during the Middle Pleistocene transition aimed at exploring the influence of climatic, ecological, and environmental instability on adaptability. Our results underscore the numerous similarities between the technological strategies of Engaji Nanyori and those of the penecontemporary sites, illustrating the uniform character of African Acheulean assemblages regardless of their temporal, geographical or environmental settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".