Influence of Intellectual Property Policies on China’s International Service Trade
Bibliographic record
Abstract
With the development of scientific and technological revolution, the service trade has played an increasingly important role in global trade. After the economic crisis in 2008, the trend of trade protectionism has arisen and the phenomenon of anti-globalization has appeared. As the largest emerging economy in the world, China should actively participate in global trade and promote the development of its service trade. Strengthening the protection of intellectual property rights can promote transnational trade. This paper aims to verify the influence and mechanism of intellectual property rights protection on China's export of service trade. The ordinary least square regression model was adopted to collect data related to the development of China's service trade and intellectual property protection in the period between 2007 to 2019 from databases including the National Bureau of Statistics of China. Based on the empirical analysis, we reached the following two conclusions: (1) There is no significant relationship between overall service trade and intellectual property protection. (2) Intellectual property protection plays a positive role in promoting manufacturing service industry, construction service industry and the charge of using intellectual property.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".