Comparative Advantage and Competitiveness of World Soy Exporter in Response to Us-China Trade Dispute
Bibliographic record
Abstract
Aim/Purpose: This research identifies China’s agricultural commodities demand on soy and compares the comparative advantage, competitiveness of world soy exporters. Background: The world’s largest agricultural commodities importer-China had bought 10.7 % of world agricultural commodities (US$1,167.2 billion) during year 2017. Studying China’s demand in order to formulate export strategies is crucial especially for BRIC countries. Methodology: Reveal Comparative advantage (RCA), Comparative Advantage above Average (CAaA) and Export Competitive Advantage (XCA) were used in this study. Findings: Analysis shows that Brazil, USA, Argentina, Canada, Paraguay, Uruguay and Ukraine who supply more than 97% of world soy export have better comparative advantage and competitiveness over other soy exporters in the world. Russia and Netherlands are picking up with offering lower export price. Impact on Society: Due to US-China Trade dispute, China has switched soy import and purchase from the US to Brazil. That has caused US$3 billion wealth loss for both countries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".