Comprehensive assessment model and method of international trade market competitiveness based on principal component analysis
Bibliographic record
Abstract
This paper takes ten economies as examples to analyze and assess the current situation of their international trade development through RCA, MS and TC indexes.On the basis of Porter's "diamond model" theory, a comprehensive evaluation index system of international trade competitiveness is set up in combination with the actual situation.The entropy value method is used to measure the comprehensive index of international trade competitiveness, and the influence of various influencing factors on international trade competitiveness is empirically studied based on the principal component multiple regression analysis.The results show that the U.S. international trade competitiveness is far ahead, with an average score of 3.67 in 2020-2024, and the lowest score is Singapore, with a score of only -2.17.The degree of explanation of international trade competitiveness of the four factors reaches 98.9%, and all of them have a promotional effect on the international trade competitiveness, in the following order: factors of production>enterprise strategy and competition>related industries>demand factors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".