Should China Join the New Trans‐Pacific Partnership?
Bibliographic record
Abstract
Abstract After President Donald Trump's ill‐advised pullout from the Trans‐Pacific Partnership (TPP) and despite the absence of the US, the remaining 11 Asian and Pacific countries agreed on a deal, renamed the Comprehensive and Progressive Agreement for Trans‐Pacific Partnership (CPTPP). The accord took effect on 30 December 2018 and provides rigorous, up‐to‐date rules for Asia‐Pacific trade, but excludes the region's two biggest economies: the US and China. In this paper, we calculate that Chinese membership in the CPTPP would yield large economic and political benefits to China and other members. The CPTPP, in its current form, would generate global income gains estimated at US$147bn annually. If China were to join, these gains would quadruple to US$632bn, or a quarter more than in the original TPP with the US. But to join the CPTPP, China would have to undertake unprecedented reforms and manage complex political challenges.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".