Bibliographic record
Abstract
Treaties are so fundamental to the lives of Native Americans and their nations in the United States and Canada that life without them would be difficult to imagine. Most contemporary issues, from land claims to resource ownership to gambling permits, are rooted in laws that derive much of their sustenance from such documents. Treaties are, therefore, vibrant documents that define important issues in our time. This book is an attempt to maintain a national conversation on the treaty basis of important contemporary laws and issues. While the texts of such treaties have long been available, discussion and other annotation in a context that gives them contemporary meaning has been scarce. This collection of essays by experts in Native American history examines these historic agreements in light of recent and ongoing controversies. Claims to ancestral land bases are one prime example: the Canandaigua Treaty of 1794 provides a context in which to address the Onondaga's claim to most of the Syracuse urban area. Treaties provide the bases for events such as the modern-day rebirth of the Ponca Nation in Nebraska more than a century after a bureaucratic error resulted in banishment from ancestral land. One chapter explores why the U.S. Army still officially regards tragic events at Wounded Knee in December 1890 as a battle, rather than a massacre. Another reveals how treaties and laws have been used to retain and regain gas and oil resource ownership. Still another expert examines why so much energy has been expended over the fate of 9,300- year-old bones that have come to be called Kennewick Man.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".