The Yearbook on International Investment Law & Policy 2008-2009
Bibliographic record
Abstract
The Yearbook on International Investment Law & Policy is an annual publication which provides a comprehensive overview of current developments in the international investment law and policy field, focusing on recent trends and issues in foreign direct investment (FDI), investment treaty practice, and investor-state arbitration.\nToday, international investment law consists of a network of multifaceted, multilayered international treaties that, in one way or another, involve virtually every country of the world. The evolution of this network continues, raising a host of issues regarding international investment law and policy, especially in the area of international investment disputes. Yearbook monitors current developments in international investment law and policy, focusing on trends in foreign direct investment (FDI), international investment agreements, and investment disputes. The Yearbook on International Investment Law & Policy 2009-2010 also looks at central issues in the contemporary discussions on international investment law and policy. With contributions by leading experts in the field, this title provides timely, authoritative information on FDI that can be used by a wide audience, including practitioners, academics, researchers, and policy makers.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.091 | 0.057 |
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".