Beyond ICSID Arbitration - The Centre for Settlement of Investment Disputes of UNASUR
Bibliographic record
Abstract
Several themes emerge in this 2014-2015 edition of the Yearbook. The first is a notable focus on country and region-specific developments. Different articles focus on key developments in such countries as Australia, Brazil, China, Ghana, India, Indonesia, Russia, and South Africa. Others focus on regional innovations, in particular in Latin America. A second area of attention is reform, and proposals for reform, in investor-state dispute settlement and in investment law generally. The third theme is the continued concern about states' regulatory autonomy and the importance of their retaining ability to protect the interests of their nationals. A fourth theme concerns the continued contribution that investment arbitration makes to the development of international law, and the influence that it is starting to have on other areas of law, whether that is as a source of inspiration in the interpretation of other norms or as a source of potentially powerful persuasive authority given the teeth that investment law has with respect to enforcement. Included are the winning memorials of the FDI Moot for both 2014 and 2015. In 2014 a team from the University of Ottawa submitted the winning claimant's memorial, while students from Harvard Law School submitted the winning respondent's memorial. In 2015, Harvard repeated its stellar performance, again winning best respondent's memorial. The winning claimant's memorial in 2015 was submitted by students from the National and Kapodistrian University of Athens. These excellent memorials reveal once again the growing interest of students in international investment law and demonstrate a striving for excellence and an enthusiasm for grappling with intellectually challenging issues.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.052 | 0.017 |
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".