Applicable Law in International Investment Arbitration
Bibliographic record
Abstract
Despite the critical importance of applicable law in international arbitration, the concept remains misunderstood and often ignored. In the field of international investment law, whether the arbitration proceedings arise from an investment treaty or from a contract, the cornerstone principle of party autonomy applies when it comes to the choice of applicable law, as provided, for example, in article 42 of the ICSID Convention. Even that principle, however, is subject to debate, for example with respect to whether initiating arbitration proceedings under an investment treaty amounts to an implicit choice of applicable law. In an attempt to clarify the notion of applicable law, this contribution first distinguishes the rules of decision, i.e. the law applicable to the specific claims submitted by an investor against a state, from incidentally applicable law, i.e. the other laws which may be relevant for the resolution of the dispute but that do not form a basis for the decision on the merits. In a second part, this contribution analyses several questions arising from the application of choice-of-law provisions in practice, with an emphasis on article 42 of the ICSID Convention. Finally, the consequences of erring in the application of the correct applicable law are examined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".