Evaluating the Social and Environmental Process of the Dene/Athabascan Migration from the Subarctic
Bibliographic record
Abstract
Approximately 1,500 years ago, Dene/Athabascans radically altered their lifestyle in central Alaska and Yukon, and many ultimately left this region entirely. In my dissertation, I evaluate the causes of this drastic transition using a multiscalar archaeological dataset that draws from excavation, geospatial, and ethnographic data. Specifically, I consider whether either a massive volcanic eruption or population change led to a sudden, wide-scale shift in Subarctic technology, diet, and trade, and an ultimate southward migration. The results of technological, isotopic, and geospatial analysis presented here strongly suggest that Dene/Athabascans responded to a regional population increase, likely driven by a shift in group organization predicated by the Dene/Athabascan kinship structure. In response, Dene/Athabascans became increasingly specialized and territorial until some Dene/Athabascans began a southward migration that finally terminated in the American Southwest over 500 years ago. The diachronic nature of my multiscalar research allows me to model this transition as a process, rather than an event, that can be compared to similar cultural processes to provide a comprehensive understanding of resilience, adaptation, and migration at different periods of history and around the world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".