\n\tNative American Lands and the Keystone Pipeline Expansion: A Legal Analysis
Bibliographic record
Abstract
\n\tMultiple branches of the U.S. government are involved in a historic legal and political battle over granting permits to a foreign corporation to expand the Keystone Pipeline. The pipeline is designed to carry tar sands oil mined in Canada across the U.S. border to refineries in the southern U.S. The planned pipeline expansion would traverse Native American lands. These lands are protected by treaties signed between the U.S. and the Great Sioux Nation. The Sioux claim that the permits that the developer of the pipeline, TransCanada, a foreign corporation, are seeking to build are being considered by the U.S. government without proper notice or permission from the Tribal Counsel in violation of the Treaties. The Native Americans have declared that if the U.S. grants the permits, it would be considered an act of war. In this evolving article, we will cover important legal issues as well as offer advice and commentary regarding Native American Lands specifically as involves the controversy surrounding the Keystone Pipeline expansion. We trust that it will shed important light on significant issues affecting all Americans and be of aid in practice and life.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".