Bibliographic record
Abstract
Investor-State arbitration under the auspices of investment treaties, both bilateral and multilateral, is burgeoning. The rate at which cases are filed is increasing, as is the rate at which tribunals are issuing decisions in those cases. Those interested in the investor-State dispute settlement process are part of an eclectic community encompassing government and private-sector lawyers, representatives of civil society, academics, international commercial arbitrators, and other students of international law. Members of this community are subjecting those decisions, as well as the wisdom and efficacy of investor-State arbitration itself, to critical and often skeptical scrutiny. The symposium convened by the UC Davis Journal of International Law and Policy was intended to contribute to the analytical scrutiny given to BITs by gathering participants from multiple disciplines and inviting them to engage in a thoughtful inquiry into a variety of topics. These included the efficacy of investment treaties, the actual functioning of investor-State arbitration, and the likely challenges and changes that investor-State dispute settlement will face in the future. Investor-state cases bring to the fore unresolved questions about the interplay between international tribunals and international law and local regulation and local dispute resolution mechanisms. The discussion at the conference, and the papers submitted by the participants that follow, are part of what promises to be a rich and continuing dialogue about the nature of investment dispute settlement.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.114 | 0.051 |
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".