The Growing Tendency of Including Investment Chapters in PTAs
Bibliographic record
Abstract
In the context of a rising number of preferential trade agreements (PTAs) that include investment protection provisions traditionally found in bilateral investment treaties (BITs), this chapter has a double purpose. First, based on an empirical analysis of 158 post-North American Free Trade Agreement (NAFTA) PTAs, we conclude that three categories of countries/regional economic integration organisations (REIOs) exist: those that regularly include investment chapters into their PTAs (Japan, the United States, Canada, the Association of Southeast Asian Nations (ASEAN), Australia and the Caribbean Community (CARICOM)), those that are finding their voice in international investment law and increasingly include such chapters (India, China, the European Union and Chile) and those that have an adverse position towards it (Brazil and the Southern Common Market (MERCOSUR)) or defer the inclusion of such provisions to further negotiations (African Plurilaterals, Morocco and South Africa). Second, we look at the drivers behind including/excluding investment protection provisions in/from PTAs. Some drivers will be readily apparent from the data collected for the purpose of answering the first question, while other drivers will need a more detailed discussion. These drivers are: (a) the weaker party accepts/uses templates of more powerful states; (b) states/REIOs wish to pursue more comprehensive and resource-friendly negotiations; (c) states/REIOs want to achieve a more coherent application of international economic law.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".