The State, Removal, and Indigenous Peoples in the United States and Mexico, 1620-2000. By Claudia B. Haake. (New York: Routledge, 2007. xiv, 293 pp. $95.00, ISBN 978-0-415-95860-8.)
Bibliographic record
Abstract
The historical literature on U.S. federal Indian policy is considerable, but studies that attempt to compare it with other national indigenous policies are rare. Claudia B. Haake offers a valuable contribution by contrasting the policies of Mexico and the United States, although the comparison is focused on the experience of only two peoples, the Delaware (Lenape) and the Yaqui (Yoeme). The temporal coverage is also more limited than the title suggests: the Yaqui are seen primarily in the Porfirian era, while much of the Delaware treatment covers the period after their arrival in Oklahoma from Kansas, around 1866. After a brief introduction, the first five chapters provide a historical summary of the Delaware experience in the United States as they move from the Delaware River area to Canada, Ohio, Indiana, Missouri, Kansas, and finally to Oklahoma to settle among the Cherokee. The next five chapters provide a similar account of the contact history of the Yaqui in Sonora and the removal of some to the Yucatan. The last three chapters are a comparative and theoretical summary and analysis of the historical sections. Removal is the common theme, but the experiences are dissimilar since, in the end, the Yaqui remain in their homeland. Such removals are common in U.S. history, but the Yaqui are relatively unique in Mexico.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".