The Bifurcation of Jurisdictional and Admissibility Objections in Investor-State Arbitration
Bibliographic record
Abstract
The practice of arbitral tribunals is notably consistent with respect to articulating the fundamental values which need to be balanced in deciding whether to bifurcate preliminary objections with respect to jurisdiction or admissibility. Moreover, there is substantial consensus on the issues or factors which ought to be evaluated by arbitral tribunals exercising their discretion under the relevant rules. What the decisions appear to lack, however, is rigorous evaluation of the likely time and costs effects of the decision to bifurcate or not. Ensuring that the parties produce information relevant to the decision whether to bifurcate rests with tribunals and the way in which they manage the proceedings before them. Tribunals ought not rely upon the parties to produce such information on their own. Instead, tribunals can and should proactively request such information in order to better carry out their judicial function. Improving the analytical rigour and depth of the analysis behind bifurcation decisions would not only improve tribunals’ conclusions, but also bolster the legitimacy of those decisions.
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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 | 0.071 | 0.124 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.012 | 0.051 |
| Scholarly communication | 0.025 | 0.023 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 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".