Neolithic and Early Bronze Age of Cis-Baikal: Spatiotemporal Patterns of Cemetery Use
Bibliographic record
Abstract
Hunter-gatherer archaeology typically focusses on the details of subsistence strategies and material culture and, in the case of cemeteries, on various aspects of mortuary practices, beliefs, and social differentiation. This paper aims to look rather at patterns of change over time and space in how past hunter-gatherer cemeteries were used from Late Mesolithic to Early Bronze Age (~8600–3500 cal BP) in the Cis-Baikal region of Eastern Siberia. The approach is based on a Kernel Density Estimate methodology applied to 560 radiocarbon dates obtained for individual burials from 65 cemeteries and representing 5 distinct mortuary traditions. This enables a number of different types of analysis to be performed at different scales: (1) It is possible to examine the overall tempo of burial events at each cemetery or a group of cemeteries; (2) Within each cemetery the spatial patterns of the sequence of graves and burials can be analyzed further; (3) It is possible to compare the different cemetery-specific chronologies within the microregional or regional context; and (4) Although tentatively at this time, the spatiotemporal pattern of cemetery use over the whole region can be visualised. The spatiotemporal analysis of individual cemeteries shows that each one had its own pattern, some very distinct and clear in their characteristics, which relate to the role the cemetery played for the local group, and within the microregional or regional population. On the regional scale some broader patterns such as shifts in frequency of burial events between microregions within mortuary traditions are visible. However, at this scale the existing sampling biases require caution in assessment of the results and future fieldwork will help improve the analysis and insights. On the other hand, many of the individual cemeteries have been excavated in full and such comprehensive datasets already provide a range of entirely new and important insights into cemetery use by the Middle Holocene hunter-gatherers of Cis-Baikal.
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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 | 0.004 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".