Bibliographic record
Abstract
How can we explain the repeated failure of U.S. and Russian leaders to “reset” their relationship since the end of the Cold War? The core cause lies in a combination of major asymmetries and incompatible policy objectives, especially about the international status of Russia’s historical borderlands. What are these structural asymmetries in contemporary American-Russian relations? ... with China: $577 billion; with Canada: $543 billion; with The Netherlands: $55 billion; with Russia: $20 billion. Beyond these structural factors, American-Russian relations must also contend with profound differences of basic policy assumptions. Both the Obama and George W. Bush administrations believed that asymmetries in power gave the United States the whip hand in the relationship. Vice President Joe Biden was closer to Dick Cheney, his predecessor, than he perhaps knew when he said in July 2009, “I think we vastly underestimate the hand we hold.”1 For the Russians, their greatest concern was that Americans consistently denied them a sphere of influence along their historical borderlands. So long as countries like Ukraine and Georgia remain eligible for NATO membership (which they have been since April 2008), Moscow cannot assume that it can provide for its regional security at the negotiating table with Washington.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".