Foreign Investment and the Environment in International Law: The Current State of Play
Bibliographic record
Abstract
By the end of 2011, the great emphasis placed by influential organisations such as the United Nations Environment Programme or the World Bank on the concept of 'green economy' suggested that the rationale for environmental protection was moving from the mere internalisation of negative environmental externalities to the spotting of green business opportunities.As I wrote then, whereas sustainable development was about doing as well in economic terms while respecting the environment, the promise of the green economy was to do better in economic terms by focusing on green business opportunities.According to some organisations, freedom of investment was to be 'harnessed' or investment (although mostly public investment) was to be shifted to promote 'green growth'.3 This message has been echoed by some visible reports, such as the Better Growth, Better Climate one, which emphasised the synergies between policies aimed at both prosperity and decarbonisation.4 At the same time, however, other organisations 5 warned that liberalising and protecting foreign investment could, in fact, thwart environmental protection at the domestic level by placing excessive bounds on the regulatory activity of States.Such warnings, which many foreign investment practitioners tended to underestimate, became more pressing in the context of the negotiation of several mega-regional agreements, and particularly the Trans-Atlantic Trade and Investment 3 See Organisation for Economic Co-operation and Development (OECD), Harnessing Freedom of Investment for Green Growth, Freedom of Investment Roundtable, 14 April 2011, available at: www.oecd.org(visited on
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.031 | 0.026 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".