LISTENING TO INVESTORS (AND OTHERS): AUDI ALTERAM PARTEM AND THE FUTURE OF INTERNATIONAL INVESTMENT LAW
Bibliographic record
Abstract
This paper inquires into an alternative foundation for investor rights linked to a theory of deliberative democracy and a procedural right to be heard. Theoretical accounts seeking to justify the rules-based system of international investment law typically rely on procedural defects in extant political systems. Investors, it is argued, are not well represented within host state political processes in which case the checking mechanism of investment arbitration provides ‘virtual representation’ to the otherwise unrepresented. The problem with this story is that it is not well supported by the empirical literature. It turns out that investors have a variety of means available to them by which they can make their preferences known to political actors or that help to mitigate the diminution of investment value as a result of political risk. This paper seeks to formulate a version of investor rights that corresponds better to concerns typically advanced to justify the investment law’s strictures, namely, that the interests of foreign investors fail to get taken into account within host states. Drawing upon historical and contemporary accounts within political theory, the project advances a justification for investor protection that is limited principally to procedural protections associated with the Latin maxim audi alteram partem. After outlining the foundations for this approach in English administrative law and political theory, the paper turns to selected arbitral awards in order to illustrate how a right to be heard would be advantageous to all of the interests involved. The project proposes bringing together theory, history, and practice in order to ground a theory of investor protection that better reconciles power, politics, and democracy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".