BG Group and "Conditions" to Arbitral Jurisdiction
Bibliographic record
Abstract
Although the Supreme Court has over the last decade generated a robust body of arbitration caselaw, its first decision in the area of investment arbitration under a Bilateral Investment Treaty was only handed down in 2014. BG Group v. Argentina was widely anticipated and has attracted much notice, and general approval, on the part of the arbitration community. In this paper we assess the Court’s decision from two different perspectives -- the first attempts to situate it in the discourse of the American law of commercial arbitration; the second considers it in light of the expectations of the international community surrounding the proper construction of Conventions between states. Our initial goal had been to write jointly, with the hope that we could bridge our differences to find, if not common, at least neighboring, ground. On some points we did so, but ultimately our divergent appreciations of the proper way to interpret the condition precedent in the investment treaty in BG Group overcame the idealism with which we commenced the project. Nonetheless we have decided to present the two papers together to emphasize the dichotomous approaches to treaty interpretation that two moderately sensible people, who inhabit overlapping but non-congruent interpretive communities, can have.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.040 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".