Bibliographic record
Abstract
From the earliest traces of first arrivals to the present, the Native peoples of North America represent a diverse and colorful array of cultures. From Central America to Canada, from recent archaeological discoveries to accounts of current controversies, this comprehensive study uses both traditional story telling and a powerful narrative to bring history to life. Johansen provides a critical narrative of European-American westward expansion through use of Native American voices, including compelling personal sketches of key figures such as: Tecumseh, alliance builder in the Ohio Valley; Chief Joseph the Younger, leader of the Nez Perce long march; and Susette LaFlesche, an Omaha Indian who reported on the Wounded Knee massacre for theOmaha-Herald. This account provides an uncommonly rich description of the material and intellectual ways in which Native American cultures have influenced the life and institutions of people across the globe, from medicine such as aspirin to foods like corn and squash to democratic ideas. It utilizes portrayals of select incidents, such as the Wounded Knee massacre and the impact of small pox, to reveal deep layers of meaning about the frontier experience in American history. A wide array of contemporary controversies, such as gambling interests, sports mascots, and sovereignty issues, are also included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".