A model of the origins and development of Aleut
Bibliographic record
Abstract
It has long been thought that Unangam Tunuu (Aleut) must have undergone substantial language contact at some point, given its divergent lexicon, features seemingly shared with Dene languages, and a single feature shared with Eyak, Tlingit, and Haida. To date, however, the nature of prehistoric language contact event(s) has remained unclear. Collaboration between the authors has resulted in a cohesive model of language contact mechanisms, together with the timing and geographical location of these contacts, allowing us to make sense of previously unexplained developments in the history and prehistory of Unangam Tunuu. We here develop an integrated archaeogenetic model consistent with existing data on archaeological and genetic patterning among northern populations to evaluate the prehistoric development of Unangam Tunuu and related languages. Climate impacts and extreme events (e.g., volcanism) have influenced these populations. We posit admixture of Proto-Aleut with Dene-speakers in southwest Alaska (Lower Kuskokwim basin) between ~4800-3700 years ago, followed by admixture with Late Anangula and Ocean Bay 2 populations in the Alaska Peninsula / Aleutian Islands and southcentral Alaska respectively between ~4000-3700 years ago. This contact and admixture altered the language of Proto-Aleut populations compared to their Proto-Inuit/Yupik relatives to the north. Proto-Aleut populations had a large geographic distribution, encompassing the Alaska Peninsula, Kodiak Island, and the Kenai Peninsula until ~1000-800 years ago, when they were replaced or assimilated by southern expansions of Yupik speakers associated with the Koniag tradition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".