Bibliographic record
Abstract
From the signing of the first bilateral investment treaty (‘BIT’) with Egypt in 1982 to the latest BIT with Rwanda in 2008, the United States (‘US’) BIT programme has produced a multitude of BITs, 40 of which are currently in force.1 Numerous US Free Trade Agreements (‘FTAs’) contain investment chapters with content very similar to the most recent US BITs. These investment chapters include, among others, Chapter 11 of the North American Free Trade Agreement (‘NAFTA’) and Chapter 10 of the Dominican Republic-Central America Free Trade Agreement (‘CAFTA-DR’). The negotiation of BITs and FTAs continues to be active. The US Government is currently in negotiations to conclude BITs with China, India, Mauritius, and Pakistan, and is exploring the possibility of BITs with Indonesia and Russia and a number of countries in sub-Saharan Africa. Negotiations to conclude the Transpacific Partnership Agreement, a proposed regional FTA between the United States, Australia, Brunei, Canada, Chile, Malaysia, Mexico, New Zealand, Peru, Singapore, and Vietnam, are in full swing.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.450 | 0.337 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".