American Indians and Popular Culture
Bibliographic record
Abstract
Americans are still fascinated by the romantic notion of the "noble savage," yet know little about the real Native peoples of North America. This two-volume work seeks to remedy that by examining stereotypes and celebrating the true cultures of American Indians today. The two-volumeAmerican Indians and Popular Cultureseeks to help readers understand American Indians by analyzing their relationships with the popular culture of the United States and Canada. Volume 1 covers media, sports, and politics, while Volume 2 covers literature, arts, and resistance. Both volumes focus on stereotypes, detailing how they were created and why they are still allowed to exist. In defining popular culture broadly to include subjects such as print advertising, politics, and science as well as literature, film, and the arts, this work offers a comprehensive guide to the important issues facing Native peoples today. Analyses draw from many disciplines and include many voices, ranging from surveys of movies and discussions of Native authors to first-person accounts from Native perspectives. Among the more intriguing subjects are the casinos that have changed the economic landscape for the tribes involved, the controversy surrounding museum treatments of American Indians, and the methods by which American Indians have fought back against pervasive ethnic stereotyping.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".