Investor-State Dispute Settlement and the Future of the Precautionary Principle
Bibliographic record
Abstract
Abstract The proliferation of bilateral investment treaties and investment chapters in trade megatreaties and the associated increase in the preference of investors for investor-state dispute settlement has given rise to concerns that the regulatory sovereignty of both developed and developing states might be compromised. In response to these concerns many trade agreements (including the recently concluded Comprehensive Economic Trade Agreement between the European Union (EU) and Canada) have incorporated provisions designed to protect the regulatory sovereignty of nation states, especially in relation to labour standards, public health, phytosanitary and environmental protection. This paper examines the nature and scope of environmental protection measures in investment chapters and attempts to analyse the extent to which these measures will, in practice, prevent challenges by investors seeking to chill or prevent environmental regulations which might threaten their investments. The analysis concentrates particularly on measures based on the precautionary principle and uses the current EU restrictions on neonicotinoid pesticides as a case study. The paper concludes that the measures included in investment chapters designed to prevent such challenges by investors will not necessarily achieve the desired level of protection for environmental regulatory sovereignty.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.016 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 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".