From Hunters to Herders in Eastern Mongolia: Long-Term Trends in Animal Hunting and Management
Bibliographic record
Abstract
Zooarchaeology or the study of animal remains from archaeological sites gives important information about many aspects of human societies in the past, including cultural practices, hunting strategies, diet, and also the environment. Here, we present the results of zooarchaeological analysis from Palaeolithic and Neolithic sites in eastern Mongolia. We show that horses were one of the most important species in all periods and that wild cattle (aurochs) became increasingly important in the Neolithic. It is also clear that both environment and hunting strategies changed beginning around 8500 cal BP, when precipitation increased and temperatures were warmer across East Asia. The types of species recovered from Neolithic sites show an increase in the range of animals hunted, specifically more focus on hard to catch prey like hare/rabbit (Leporids), foxes, and even birds. Species diversity decreased again in the Bronze Age with the introduction of domesticated herd animals. The results show that relationships between humans, herds, and grasslands were fundamental to the development of Mongolian society, regardless of climate change. We should envision the three pillars of pastoralism – herder-pasture-livestock – as fundamental to sustainable subsistence in Mongolia with its roots stretching back to the Palaeolithic.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".