Sky loom: Native American myth, story, and song
Bibliographic record
Abstract
Sky Loom offers a dazzling introduction to Native American myths, stories, and songs drawn from previous collections by acclaimed translator and poet Brian Swann. With a general introduction by Swann, Sky Loom is a stunning collection that provides a glimpse into the intricacies and beauties of story and myth, placing them in their cultural, historical, and linguistic contexts. Each of the twenty-six selections is translated and introduced by a well-known expert on Native oral literatures and offers entry into the cultures and traditions of several different tribes and bands, including the Yupiit and the Tlingits of the polar North; the Coast Salish and the Kwakwaka'wakw of the Pacific Northwest; the Navajos, the Pimas, and the Yaquis of the Southwest; the Lakota Sioux and the Plains Crees of the Great Plains; the Ojibwes of the Great Lakes; the Naskapis and the Eastern Crees of the Hudson Bay area in Canada; and the Munsees of the Northeast. Sky Loom takes the reader on a wide-ranging journey through literary traditions older than the discovery of the New 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.009 |
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".