Using Arbitration for Resolving Foreign Investment Disputes: A Comparative Study of Laws on Arbitration in Ghana and China
Bibliographic record
Abstract
International Investment in recent times is seen as one of the fastest-developing areas of international law. In the past decades, there has been a dramatic increase in the number of bilateral investment treaties and other agreements with investment related provisions that grant foreign investors important substantive and procedural rights, including, most importantly, the right to sue individuals, organizations and even the state hosting their investment for violations of customary international law and treaty obligations. Dispute becomes an inevitable phenomenon as individuals, organizations and countries continue to engage in foreign investment and as such there is the need for dispute solving mechanism to resolve such disputes as and when they arises. Even though there are several dispute solving mechanisms, arbitration seems to be a well-established and widely used mechanism to end dispute probably due to the efficiency and flexibility nature of it. The laws governing arbitration differ from one country to the other and it is for this reason that investors need to be abreast with the different arbitration laws so as to enable them make inform decisions as to whether to resort to arbitration or not. This paper analyses the arbitration laws of The Republic of Ghana and Peoples Republic of China in a comparative manner by drawing on the similarities and difference with respect to arbitration laws and procedure in these two countries. The paper is divided into three parts. The first part of this paper gives a brief background as well as the characteristics of the concept of arbitration. The second part looks as the similarities and difference of arbitration between the selected countries, and the final part looks at the arbitration phase and post arbitration phase of the two countries.
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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 | 0.006 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".