Landscape Traveled by Coyote and Crane: The World of the Schitsu'umsh (Coeur d'Alene Indians)
Bibliographic record
Abstract
Anthropologist Rodney Frey culminates a decade of work with the Schitsu'umsh (the Coeur d'Alene Indians of Idaho) in this portrait of the unique bonds between a people and the landscape of their traditional homeland. The result of an intensive collaboration between investigator and Native people, the book includes many traditional stories that invite the reader's participation in the world of the Schitsu'umsh. The Schitsu'umsh landscape of lake and mountains is described with a richness that emphasises its essential material and spiritual qualities. The historical trauma of the Schitsu'umsh, stemming from their nineteenth-century contacts with Euro-American culture, is given dramatic weight. Nonetheless, examples of adaptation and continuity in traditional cultural expression, rather than destruction and discontinuity, are the most conspicuous features of this vivid ethnographic portrait. Drawing on pivotal oral traditions, Frey mirrors the Schitsu'umsh world view in his organisation and presentation of ethnographic material. He uses first-person accounts by his Native consultants to convey crucial cultural perspectives and practices. Because of its unusual methodology, Landscape Traveled by Coyote and Crane is likely to become a model for future work with Native American peoples, within the Plateau region and beyond.
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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 | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".