Implications of New U.S.-China Deal, Soybean Commitments, Port Fee Suspension, and SE Asia Deals
Bibliographic record
Abstract
The November 2025 NDSU Agricultural Trade Monitor finds a measured thaw in U.S.-China farm trade and tentative openings in Southeast Asia. Beijing has lifted the March 2025 retaliatory tariffs on U.S. agriculture but kept a 10 percent reciprocal tariff in place, and the deal swaps dollar targets for explicit soybean volumes: 12 MMT in 2025/26 and a 25 MMT annual floor in 2026–2028, totaling 87 MMT, supportive yet still below pre-2018 norms and subject to opaque compliance. The report emphasizes that China’s purchases typically follow U.S.-Brazil price spreads, implying that actual liftings will hinge more on competitiveness than on fixed quotas. Markets responded as soybean futures moved above 11 dollars per bushel, while sorghum and wheat firmed on expectations of renewed Chinese demand; cash soybean basis strengthened 40 to 50 cents from September lows but remains weaker than historical norms. A one-year suspension of Section 301 port fees effective November 10 averts an estimated 2.3 billion dollars in shipping costs and removes a 5 to 7 cents per bushel headwind on bulk grains, partially restoring U.S. freight competitiveness that had eroded versus Canada and Brazil. Beyond China, new market-access arrangements with Thailand, Malaysia, Cambodia, and Vietnam could lift oilseed and feed shipments, but the headline 19 MMT soybean pledge lacks detail and may largely formalize existing flows rather than add new demand. Net effect: a modest recovery in U.S. agricultural trade with China and Southeast Asia, tempered by Brazil’s export dominance and a structurally tighter U.S. exportable surplus as domestic crush expands.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 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".