International Investment Agreements Between Developed and Developing Countries: Dancing with the Devil? Case Comment on the Vivendi, Sempra and Enron Awards
Bibliographic record
Abstract
International investment agreements can have detrimental effects for developing countries: they can limit a government’s ability to regulate in the public interest where this interest runs counter to that of foreign investors; they can severely restrict a country’s ability to enact measures responding to financial, social, and economic crises; and they can impede legitimate democratic processes. Three recent arbitral decisions at the International Centre for Settlement of Investment Disputes — Compania de Aguas del Aconquija S.A. v. Argentina, Sempra Energy International v. Argentina, and Enron v. Argentina — demonstrate these risks. This comment examines how these tribunals have negatively impacted Argentina through their interpretations of expropriation law, the fair and equitable treatment principle, and equitable defences such as necessity, as well as through the tribunals’ willingness to interpret Argentine law. The author proposes that future international investment tribunals apply a sustainable development analysis to avoid similar outcomes. Such an analysis would consider promoting investment not as an end in itself, but as part of a country’s approach to important social issues, including promoting human rights, protecting the environment, and improving social welfare. In advancing this proposal, the author explores the legal and equitable basis for applying sustainable development law when interpreting international investment 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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".