The Developments of ISDS Mechanism Initiated by the EU Investment Court System and China’s Choice
Bibliographic record
Abstract
The European Union has initiated fundamental transformations to the existing investor-state dispute settlement (“ISDS”) mechanism by introducing the investment court system (“ICS”) in recently concluded the 2016 EU-Canada FTA and the 2016 EU-Vietnam FTA, as well as the 2015 TTIP Proposal. Furthermore, the EU also proposed a more comprehensive proposal for a multilateral investment court (“MIC”), which may lead to significant impacts on the ISDS reform. China has become one of the world’s biggest recipients and sources of foreign direct investment, and has more concerns regarding ISDS reform than before. By now, China has not clarified its proposal on ISDS reform. Given the “American First” policy and the intense relationship between U.S. and China in trade and investment, both the EU and China consider the BIT negotiations as the breakthrough point. Recently, in light of the EU’s ambition for a 2020 deadline for an EU-China BIT negotiation, the Foreign Investment Law of China was passed by the National People’s Congress on 15 March 2019 which provides higher standards investment protection for foreign investors, as well as the Premier Minister of China, Keqiang Li’s proposed visit to the Summit with EU leader on 9 April 2019 are signals to accelerate EU-China BIT negotiations ahead of expected passage. Whether China will adopt the ICS mechanism in the EU-China BIT, and whether China will expand the ICS mechanism in the ongoing China-Japan-Korea FTA and Regional Comprehensive Economic Partnership (“RCEP”) are important not only for these BITs/FTAs, but also for the future of the ICS mechanism or even MIC.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".