Bibliographic record
Abstract
Launched in November 2014, this project is addressing a central policy issue of contemporary international investment protection law: is investor-state arbitration (ISA) suitable between developed liberal democratic countries?The project will seek to establish how many agreements exist or are planned between economically developed liberal democracies.It will review legal and policy reactions to investorstate arbitrations taking place within these countries and summarize the substantive grounds upon which claims are being made and their impact on public policy making by governments.The project will review, critically assess and critique arguments made in favour and against the growing use of ISA between developed democracies -paying particular attention to Canada, the European Union, Japan, Korea, the United States and Australia, where civil society groups and academic critics have come out against ISA.The project will examine the arguments that investor-state disputes are best left to the national courts in the subject jurisdiction.It will also examine whether domestic law in the countries examined gives the foreign investor rights of action before the domestic courts against the government, equivalent to those provided by contemporary investment protection agreements.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".