<i>Lone Pine Resources v Canada Award</i>: Steps towards a Recognition of Sustainable Development Principles in Energy Investment Arbitrations
Bibliographic record
Abstract
Lone Pine Resources Inc. v. The Government of Canada 1 is the first investment arbitration case in the oil and gas sector in which the host state has taken measures to enforce its domestic sustainable development laws and regulations. In this case, the Canadian government prohibited fracking in the St. Lawrence River basin in Quebec, despite having previously issued a permit, by placing the precautionary principle, which is a principle of sustainable development, as the criterion. The tribunal did not find the host government's action to be a violation of the investor's rights, although it was unable to answer the question of whether the implementation of the precautionary principle constitutes a public purpose according to the NAFTA expropriation standard. However, it is notable that in the submissions of the parties and amicus curiae, reference has been made to the precautionary principle on the basis of applicable domestic and international law. Another feature of this case is that the arbitral tribunal decided to grant the request for participation of amicus curiae by an environmental NGO, and in distinct sections of the final award, it mentioned the views of the environmental group. The implementation of sustainable development is crucial in the field of petroleum arbitrations, given the extent of environmental degradation caused by these projects. Even though this case pertains to North America, it may mark the beginning of a global transformation that affects the petroleum producing countries throughout the world. Additionally, it may open a door for arbitration tribunals to establish compatibility between the standards of investor protection and sustainable development principles such as precaution and public participation.
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 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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.020 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.019 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".