Thawing a Frozen Treaty: Protecting United States Interests in the Arctic with a Congressional-Executive Agreement on the Law of the Sea
Bibliographic record
Abstract
The steadily shrinking Arctic ice cap has triggered a feverish interest among the five nations whose coastlines border the region concerning their respective rights to the ocean and the seabed below. The possibility of huge reserves of natural gas and oil, and the potential for newly navigable channels have led to competing claims by the United States, Canada, Russia, Denmark, and Norway over large sections of the Arctic. The United States, however, is in danger of losing out due to the obstructionist efforts of a handful of isolationist Senators who consigned a crucial treaty providing a mechanism to negotiate these claims to the deep freeze of the United States Senate for nearly twelve years. While the other Arctic nations have long since ratified the treaty and are proceeding to stake out the future of the region, the United States remains seated on the sidelines.\nDespite the unanimous support of the Senate Foreign Relations Committee and the backing of the current administration, Senate leaders, under pressure from a small cadre of anti-internationalist Senators, have declined to schedule a floor vote on the Law of the Sea. It is time for a new approach that will free this critical law from its icy prison. The president should withdraw the treaty from the Senate and work with both Houses of Congress to foster a Congressional- Executive agreement to ensure that America is not left out in the cold.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".