An Empirical Study on the Situation and Determinants of Intra-industry Trade in China's Textile and Apparel Industry
Bibliographic record
Abstract
This paper examines the presents situation and determinants of intra-industry textile and clothing trade from 2002 to 2010 in China.The results show that the common level of intra-industry trade on China's TA industries is very low,the development of which is very slow,and the style of trade on China's TA industries is mainly inter-industry trade.Also,on the product level,the level of intra-industry trade is different,and it shows that IIT is the main type,which needs improvement.IIT is found to be positively related to the country-specific variables,such as the market size,per capita income level,exchange rate,and negatively to the geographic proximity of the partners.Economies of scale are seen to have a positive influence on IIT and HIIT,but a negative relationship with VIIT.Although the relative openness of a country's trade regime shows no significant relationship with any form of IIT,a trade imbalance does affect TIIT,HIIT and VIIT flows.Finally it gives some competitiveness-fostering suggestions for the development of China's TA intra-industry trade.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".