Bibliographic record
Abstract
The U.S.-Japan relationship is a longterm one involving mutually accepted principles -regional economic and political stability; market-driven economies; and democratic systems of government.The relationship is also complex, encompassing many factors.The United States and Japan are closely tied economically.Japan ranks third to Canada and Mexico as the largest single-country market for U.S. exports.Japan is the leading market for U.S. agricultural exports.Japan is also the second largest supplier of U.S. imports.The United States ranks as Japan's number one export market and import supplier.The two economies are also tied by financial capital flows.Despite, or perhaps because of, the interdependence, U.S.-Japan ties have been burdened by friction for many years.In the late 1960s and the 1970s, these tensions derived from the growth in competition from Japanese imports, first in labor-intensive goods, such as wearing apparel, then later in more capitalintensive goods, such as steel and cars.Since the 1980s, as U.S. competitiveness in these industries improved and/or as Japan's competitiveness lessened, the emphasis of U.S. concerns shifted to market access in Japan for U.S.-made products, such as agricultural products, semiconductors, cars and autoparts, and insurance.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.719 | 0.692 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".