Entangled with Antlers on the Iamal Peninsula of Arctic Siberia
Bibliographic record
Abstract
Indigenous communities living in the Iamal-Nenets region of the Arctic Siberia incorporate reindeer antlers into various aspects of their lives, at times in remarkable ways. This is especially the case for Nenets herding families, who closely interact with domestic reindeer on a daily basis. Antlers for Nenets are not just raw materials for producing tools, but rather a part of their perceptions of time, clothing designs, gendered skills and spaces, and physical manifestations of pride. This article links current Nenets entanglements with antler to similar material practices on the Iamal Peninsula during the Iron Age. To accomplish this, we incorporate multi-generational Nenets knowledge into the analysis of modified and unmodified antler recovered during excavations of Iarte VI, an Iron Age archaeological site located on the tundra of the Iamal Peninsula. Our approach is founded upon direct engagement and collaboration with Nenets families from the Iamal region. Together, we focus on identification of reindeer age and sex through visual assessment of antler objects from Iarte VI. We also explore antler shapes and growth cycles, working qualities, and placement within and outside dwelling areas at the site. This collaborative approach sheds light on site seasonality, the ages and genders of the inhabitants of Iarte VI, and several longstanding continuities in antler practices.
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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 | 0.001 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".