Bibliographic record
Abstract
This article is based on the EFILA’S ‘Inaugural’ Annual Lecture 2015. ISDS in its current international arbitration format has attracted criticism. In response, the EU proposal for ISDS in the TTIP consists of a two-tiered court system, comprising an appeal mechanism empowered to review first-instance decisions on both factual and legal grounds and, the EU says, paving the way for a “multilateral investment court”. The Lecture expressed surprise at the EU proposal of a court mechanism given the CJEU’S unambiguous, historical unease with other similar, parallel international court systems. The Lecture proposed a third way, aimed at addressing these concerns, whereby a Committee – stroke – Interpretive Body, informed by the intentions of the TTIP Parties, would take over the development of TTIP jurisprudence in a more linear and consistent manner, with a longer-term view, whilst ad hoc arbitration tribunals in their current form would focus on the settlement of the discrete factual dispute. Since the Lecture was delivered, the ICS was adopted in both the EU–Vietnam FTA and (in part) the EU–Canada CETA. This contribution ponders how the ICS might work in practice, sit alongside current ISDS tribunals, and contribute to development and jurisprudence in the field.
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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 | 0.046 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.020 | 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".