Bibliographic record
Abstract
The tangled, complex history of the relationship between the United States government and Native American peoples in the twentieth century is still understudied and often misunderstood. Any publication that increases our grasp of any significant aspect of that history is welcome. John Fahey's account of the career of the Coeur d'Alene leader Joe Garry, who was an important figure in the National Congress of American Indians (NCAI) in the 1950s and 1960s, provides us with useful information and insights about the activities of the NCAI, perhaps the most important national-level Indian organization during those decades, and about the local level struggle between Garry's community and the government, which led him onto the national scene. The key issue that energized the NCAI, brought it to some prominence, and increased the number of tribes actively involved in the organization's activities was termination, the proposed ending of the reservation system and the division of a tribe's assets among its individual members. To the bureaucrats and politicians pushing termination, it meant ending the Indian' status as “wards of the government” and putting them on a footing similar to that of other Americans. To the Indian and other opponents of termination, it meant the end of the Indian way of life as they knew it and the breaking of promises and undertakings contained in numerous treaties.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".