A tale of policy carve-outs and general exceptions: <i>Eco Oro v Colombia</i> as a case study
Bibliographic record
Abstract
ABSTRACT The Eco Oro v. Colombia Decision has garnered immediate public and academic attention and generated immense controversy. One of the reasons for its notoriety was the arbitral tribunal’s unconventional take on the general exceptions clause of the Canada–Colombia Free Trade Agreement and its contention that, even when a challenged measure fulfils the requirements of this exception, a host state’s duty to compensate remained. This conclusion has since been interpreted as an indication that, in spite of states’ attempts to carve certain regulatory and/or administrative measures motivated by public interest out of the protective scope of some recent international investment agreements (IIAs), such as environmental protection, arbitral tribunals continue to disregard these sensitivities. In light of this background, this article will focus on the parties’ arguments, the Tribunal’s analysis, as well as the interpretative implications of the Decision, focusing on indirect expropriation, the fair and equitable treatment, and the application of the general exception clause.
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 | 0.001 | 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) | 0.001 | 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".