Cannibalism versus funerary defleshing and disarticulation after a period of decay: comparisons of bone modifications from four prehistoric sites
Bibliographic record
Abstract
OBJECTIVES: Humanly induced modifications on human and non-human bones from four archaeological sites of known funerary rituals (one interpreted as cannibalism and three interpreted as funerary defleshing and disarticulation after a period of decay) were analyzed to ascertain whether macromorphological and micromorphological characteristics of cut marks can be used to distinguish cannibalistic from secondary burial practices. MATERIAL AND METHODS: Four collections were analyzed: the Magdalenian assemblage from Gough's Cave (UK) and the Mesolithic-Neolithic bone samples from Lepenski Vir, Padina and Vlasac (Serbia). A total of 647 cut marks (345 on human and 302 on non-human remains) were imaged and measured using an optical surface measurement system, the Alicona InfiniteFocus, housed at the Natural History Museum (London, UK). RESULTS: The frequency of cut marks at Gough's Cave exceeds 65%, while it is below 1% in the Serbian sites, and no human tooth marks and only one case of percussion damage have been observed on the three Serbian collections. The distribution of cut marks on human bones is comparable in the four assemblages. Cannibalized human remains, however, present a uniform cut mark distribution, which can be associated with disarticulation of persistent and labile articulations, and the scalping and filleting of muscles. For secondary burials where modification occurred after a period of decay, disarticulation marks are less common and the disarticulation of labile joints is rare. The micromorphometric analyses of cut marks on human and non-human remains suggest that cut marks produced when cleaning partially decayed bodies are significantly different from cut marks produced during butchery of fresh bodies. CONCLUSIONS: A distinction between cannibalism and secondary treatment of human bodies can be made based on frequency, distribution and micromorphometric characteristics of cut marks.
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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 | 0.003 | 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) | 0.001 | 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".