The International Court System: A Solution to the Crisis in Investor-State Arbitration?
Bibliographic record
Abstract
Most known investor-state disputes are referred to a form of international arbitration known as investor-state arbitration (ISA) or investor-state dispute settlement (ISDS). The rest are referred to domestic arbitration or litigation before the courts of host states. The International Centre for Settlement of Investment Disputes (ICSID) is the largest ISDS institution, having handled 829 out of 1190 cases by December 2021. However, in recent years the ISDS regime has faced challenges that have reached crisis proportions. States have responded to these challenges in different ways. For example, during 2014 the European Union (EU) intended to provide for ISDS in its anticipated trade agreements with the United States of America and Canada. In preparation the EU held public consultations wherein the public was invited to comment on whether ISDS could be used in these agreements. Over 90 per cent of the voters rejected the inclusion of ISDS therein. In response the EU abandoned ISDS and created a bilateral Investment Court System (ICS). The final death knell for ISDS in the EU came in 2018 and 2021 when the Court of Justice of the European Union (CJEU) ruled that ISDS among EU states is unlawful and incompatible with its legal order. This paper aims to assess the legal nature of the ICS, as well as whether the ICS can resolve the challenges that face ISDS worldwide. The paper concludes that firstly, the ICS is a hybrid of a court and a tribunal; secondly, that the ICS fails to fully address all the challenges faced by ISDS. It is a work in progress that must be interrogated further and be improved upon over time.
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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 | 0.018 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.028 | 0.030 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".