Human Rights Promotion through Transnational Investment Regimes: An International Political Economy Approach
Bibliographic record
Abstract
International investment agreements are foundational instruments in a transnational investment regime that governs how states regulate the foreign-owned assets and the foreign investment activities of private actors. Over 3,000 investment agreements between states govern key governmental powers and form the basis for an emerging transnational investment regime. This transnational regime significantly decentralizes, denationalizes, and privatizes decision-making and policy choices over foreign investment. Investment agreements set limits to state action in a number of areas of vital public concern, including the protection of human and labour rights, the environment, and sustainable development. They determine the distribution of power between foreign investors and host states and their societies. However, the societies in which they operate seldom have any input into the terms or operation of these agreements, raising crucial questions of their democratic legitimacy as mechanisms of governance. This paper draws on political science and law to explore the political economy of international investment agreements and asks whether these agreements are potential vehicles for promoting international human rights. The analysis provides an historical account of the investment regime, while a review of the political economy of international investment agreements identifies what appears to be a paradox at the core of their operation. It then examines contract theory for insight into this apparent paradox and considers whether investment agreements are suitable mechanisms for advancing international human rights.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".