Lacustrine geoarchaeology in the central Kalahari: Implications for Middle Stone Age behaviour and adaptation in dryland conditions
Bibliographic record
Abstract
The Middle Stone Age (MSA) was a time of great human adaptation and innovation. In southern Africa, coastal locations have been viewed as key places for the development of human resource use and behaviour, with the dryness of the continental interior after c.130 ka regarded as both an obstacle to occupation and a limit on behaviour. Newly excavated MSA sites on the floor of the now-dry palaeolake Makgadikgadi basin, central Botswana, along with accompanying environmental data, have provided a significant opportunity to reassess the nature of MSA adaptation to, and behaviour under, dry conditions. Excavated sites dated to 80–72 ka and post 57 ka reveal purposeful early human use of an extensive 60,000 km 2 lacustrine basin during dry, as opposed to lake-high, phases, as well as highlighting movement strategies for tool-making resource procurement. Findings have significant implications for theories of early human mobility and innovation, as well as for understanding the drivers, constraints and opportunities for the use of drylands. The deliberate selective movement of lithic raw materials within the basin for artefact manufacture evidences thoughtful adaptation to dry conditions within the lake basin. This research shows that open-air sites in the Kalahari drylands of central southern Africa can make important contributions to debates surrounding the development of human-environment relationships during the MSA, as well as challenging narratives of a hostile and largely empty landscape.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".