Chemical evidence for milk, meat, and marine resource processing in Later Stone Age pots from Namaqualand, South Africa
Bibliographic record
Abstract
The subsistence practices of Later Stone Age (LSA) foragers and herders living in Namaqualand South Africa are often difficult to differentiate based on their archaeological signatures but characterizing their dietary choices is vital to understand the economic importance of domesticates. However, ethnohistoric accounts have provided information on the cooking/boiling of marine mammal fat, mutton, plants, and milk by early herders and foragers across the Western Cape. To further investigate these reports, we use lipid residue analysis to characterize 106 potsherds from four open-air LSA sites, spanning in time from the early first millennium to the late second millennium AD. Two sites (SK2005/057A, SK2006/026) are located on the Atlantic coast whereas sites Jakkalsberg K and Jakkalsberg M are located further inland on the southern bank of the Orange River. Notably, at the coastal sites, the presence of marine biomarkers suggests the intensive and/or specialized processing of marine products in many vessels. The dominance of ruminant carcass products at inland sites and probable sheep remains confirms the importance of stockkeeping. Furthermore, and in good agreement with ethnohistoric accounts for its use, our results provide the first direct chemical evidence for the use of dairy products in LSA western South Africa.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".