Rise of trade protectionism: the case of US-Sino trade war
Bibliographic record
Abstract
In recent decades, China experienced the fastest economic growth by opening its economy and focussing on trade and is now the second largest economy surpassing Japan. The widening of the US trade deficit with China raised tensions between the two largest economies of the world. Although China is gradually opening, it is still protecting some of its industries and engaging in unfair trade practices. Trump administration argues that trade deficit hurts US manufacturing and promised to cut them. Previous administration used the WTO process to challenge China for abusing intellectual property rights, import restrictions, and subsidising its industries. Protectionism hurts both countries. USA is the largest trade partner of China and US tariffs can slow its growth. China’s tariffs on US goods also are raising prices for consumers. Moreover, studies indicate that unilateral measures of imposing tariffs neither reduce deficits nor create jobs.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| 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".