An Evaluation of the Need and Cost of Selected Trade Facilitation Measures in China: Implications for the WTO Negotiations on Trade Facilitation
Bibliographic record
Abstract
In 2004, China became the third largest trading economy in the world. Although official overall average import tariff rate was reduced to 9.9% as of January 2005, actual tariff rates are likely much lower. Although further tariff reductions may lead to renewed and expanded global trade growth, trade facilitation will play an increasingly important role in promoting global trade. Costs associated with implementation of trade facilitation measures may be classified into four categories: new regulations, institutional changes, training, and equipment and infrastructure. The study was generally not able to determine costs of specific trade facilitation measures in China. However, Customs and the General Administration of Quality Supervision, Inspection and Quarantine (AQSIQ) are the two government departments that are most deeply involved in trade facilitation, and a review of their expenditures in this field provides useful information on equipment/infrastructure costs that may be associated with implementing modern trade facilitation systems.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".