Researching International Norm Diffusion: Brazilian and Latin American Resistance to Investor-State Dispute Settlement
Bibliographic record
Abstract
Since the ISA's overarching theme for this conference is norm diffusion, we will address a specific, dual issue -- foreign-investment protection agreements (FIPAs), which governments adopt when they ratify these documents, and investor-state dispute settlement (ISDS) processes, which establish arbitration mechanisms that a transnational corporation can use to seek compensation from signatory states for any violation of its new privileges.These rights are far from uncontroversial, since ISDS processes have imposed enormous penalties on signatory states, particularly the weak, foreign-investment receiving countries in the Third World. Because these awards are so high, considerable resistance has been growing to reject what is seen as a new form of imperialist domination. We will limit our discussion of the new resistance to this process of norm diffusion to a specific region, Latin America, where the contestation of new rights for transnational corporations (TNCs) is encountering significant resistance not just within civil society but at the highest political levels.Our analysis is divided into two parts. The first addresses the conceptual and methodological issues facing scholarship on norm diffusion in general and research on enhanced TNC rights in particular. Our text’s second part will explore the resistance offered, first, by Brazil, second, by smaller Latin American countries, and, third, by the continent’s two main evolving regional structures, Mercosur and UNASUR.
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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 | 0.026 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".