Excavations at the Stone Age Site of Nyabusora in the western Lake Victoria-Nyanza Basin, Tanzania
Bibliographic record
Abstract
Abstract This paper presents excavation results from Nyabusora, northern Tanzania, conducted by M. Posnansky and W.W. Bishop (1959) and M. Posnansky (1961). Only preliminary reports have previously been published. It synthesises the site’s history, incorporating previously unpublished analyses and information from Posnansky’s original field notes, and presents new 2014 field survey results and new archival research. Nyabusora holds particular significance as the only Early to Middle Stone Age (ESA/MSA) site in the region to have yielded both lithic and faunal remains, which gain new relevance in light of recent developments in ESA/MSA archaeology in eastern Africa. Nyabusora’s ‘Sangoan’ lithic assemblage is now largely decontextualised and associated finds have been lost, so this study presents the only available lithic and faunal analyses, alongside interpretations of the stratigraphic sequence and site. Such stratified assemblages are exceptionally rare and are generally attributed to the Middle Pleistocene. This research enhances understanding of Plio-Pleistocene landscape evolution in the Kagera River and western Lake Victoria-Nyanza Basin. It contributes important new data on ESA/MSA lithic variability and, via ongoing investigations by Basell within the Kagera catchment, offers huge potential for clarifying Middle Pleistocene palaeoenvironments.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".