It Takes Two to Tango: Regional Investment Treaties and Investor Protection on Both Sides of the Atlantic
Bibliographic record
Abstract
In 2009, the Treaty of Lisbon conferred the European Union the exclusive competence on foreign direct investments in Art. 207 TFEU. Together with the common commercial policy, it is now one of the main pillars of the external action of the EU. The Union has seen this new competence as good opportunity to carry out a comprehensive regulation of trade and investment issues at the European level and has applied it in the negotiation of a series of investment agreements with other States such as Canada, the United States, Vietnam, and Singapore. An intense public debate has arisen on the opportunity of entering into these agreements and whether they should include references to arbitration as an investor-state dispute settlement mechanism (ISDS). The context to this is the growing opposition to the traditional mechanisms of ISDS in some Member States and sectors of the civil society. Meanwhile, in the US, there has also been growing public opinion opposing investment treaties and external and parallel mechanisms of investor protection from both sides of the political spectrum and for various reasons. Prior to the 2016 Presidential Elections, prominent democrats opposed the Trans-Pacific Partnership (TPP) as long as ISDS mechanisms were included. The present article includes an analysis of trade policymaking in the US and the attitude of the US Congress to new mega-regionals and new investment treaties. Being a major issue in Europe, it focuses, in particular, on the policy position concerning ISDS as the method of choice for resolving disputes between investors and the host countries.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".