Can International Investment Agreements Be Instruments of Sustainable Development? Systemic Capacity Challenges for Developing Countries
Bibliographic record
Abstract
The world is girdled by a dense network of international investment agreements (IIAs). IIAs are not well-designed to promote investment, much less to contribute to sustainable development. Existing IIAs contain mainly broadly-worded investor protection provisions enforceable through investor-state arbitration. Despite IIAs’ strong investor protections, however, investment inducing effects have not been clearly demonstrated. As well, investor protections have been interpreted in some investor-state cases to constrain the ability of states to regulate to achieve sustainable development. Experience with investor-state arbitration and the changing context in which IIAs are being negotiated has created an awareness of the strong bite of IIAs and encouraged increasing innovation in treaty models and some actual treaties that enhance the prospect that they will contribute to investment-led sustainable development. But many challenges impair the ability of countries, especially developing countries, to ensure that the treaties they sign support their sustainable development in light of their distinctive circumstances. In some cases, this is due to a lack of the technical capacity to assess the desirability of particular kinds of provisions, despite capacity building efforts of UNCTAD, the World Bank, and NGOs. As well, power imbalances continue to define the outcome of treaty negotiations between developed and developing countries. For many developing countries, competition for investment with similarly situated countries may also discourage an aggressive approach to IIA negotiations. This paper surveys some of the continuing systemic challenges for developing countries regarding the negotiation of and compliance with investment treaty obligations.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.018 | 0.027 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 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".