China-Measures Related to the Exportation of Various Raw Materials: Dispute Focuses and Losing Causes
Bibliographic record
Abstract
China-Measures Related to the Exportation of Various Raw Materials Caseis another China’s lost case following the losing ofChina and US Tyres Case.China is charged for violating relevant obligations of China’s Accession Protocol and the GATT by imposing export restrictions on nine kinds of raw materials.While China invokes Article XX(b) and(g) of the GATT 1994 for reasons that export restrictions imposed on the raw materials is for the purpose of protecting human,animal or plant life or health;or protecting environment and exhaustible natural resources.It’s a pity that the decision of this case is of no benefit to China because the panel uses mechanical and strict interpretations in relevant articles.However,China lacks proof and its legal documents and domestic relevant legislations and policies have many problems which need to be summed up and counterconsidered.In that case,China can effectively respond to the future litigation under the WTO.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".