Maritime adaptations and dietary variation in prehistoric Western Alaska: Stable isotope analysis of permafrost‐preserved human hair
Bibliographic record
Abstract
The reconstruction of diet and subsistence strategies is integral in understanding early human colonizations and cultural adaptations, especially in the Arctic-one of the last areas of North America to be permanently inhabited. However, evidence for early subsistence practices in Western Alaska varies, particularly with regards to the emergence, importance, and intensity of sea mammal hunting. Here, we present stable carbon and nitrogen isotope data from permafrost-preserved human hair from two new prehistoric sites in Western Alaska, providing a direct measure of diet. The isotope evidence indicates a heavy reliance on sea mammal protein among the earlier Norton-period group (1,750 ± 40 cal BP), confirming that the complex hunting technologies required to intensively exploit these animals were most likely already in place in this region by at least the beginning of 1st millennium AD. In contrast, analysis of the more recent Thule-period hair samples (650 ± 40 cal BP; 570 ± 30 cal BP) reveals a more mixed diet, including terrestrial animal protein. Sequential isotope analysis of two longer human hair locks indicates seasonal differences in diet in a single Norton-period individual but demonstrates little dietary variation in a Thule-period individual. These analyses provide direct evidence for dietary differences among Alaska's early Eskimo groups and confirm the antiquity of specialized sea mammal hunting and procurement technologies. The results of this study have implications for our understanding of human adaptation to maritime and high-latitude environments, and the geographical and temporal complexity in early Arctic subsistence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".