Eskimo languages in Asia, 1791 on, and the Wrangel Island-Point Hope connection
Bibliographic record
Abstract
Merck’s statement about four “Sedentary Chukchi” (Eskimo) languages or language varieties along the coast of Chukotka in 1791 is thoroughly remarkable and worthy of careful interpretation. By his statement of their geographical distribution, the first three languages are very easy to identify, as 1) Sirenikski, 2) Central Siberian Yupik, explicitly including St. Lawrence Island, and 3) Naukanski. Merck’s language number four, “Uwelenski” he claims, startlingly, to be spoken along the Arctic Coast of Chukotka from Uelen as far as Shelagski Cape, 600 miles to the northwest. Serendipitously enough, Merck has 70 or so ”Uwelenski” words of cultural interest transcribed throughout his text. Careful studies of these words by this writer and also by Mikhail Chlenov show that “Uwelenski” is in fact a dialect of Central Siberian Yupik, thus part of a language continuum spoken from St. Lawrence Island to the Chaplino corner and the East coast of Chukotka, thence to the North coast of that mainland, treating Naukan as a “third Diomede” rather than as a mainland interruption. However there is no evidence that language number four, “Uwelenski,” actually a dialect of Merck’s language number two, was spoken beyond Kolyuchin Bay. Beyond that point, however, there was indeed a fourth Eskimo language. The second half of the paper concludes, from at least seven independent sources, that that fourth language was in fact none other than North Alaskan Inupiaq, spoken intermittently in pockets between Kolyuchin and Shelagski Cape, at least since the opening of Russian posts at Kolyma and into the nineteenth century, by north Alaskans from the Point Hope area, who also used Wrangel Island as a stopping place.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".