Long Rang Trans-Boundary Air Polution Smelter Case Arbitration Outcome
Bibliographic record
Abstract
The purpose of the investment is to bring benefits to the owners and sustainable development for the local community and for future generations. Arbitration is the process of resolving legal disputes between individuals, groups and countries. Every investment activity must ensure sustainable development to respect the rights of future generations. However; Canadian zinc smelting companies emit sulfur dioxide and cause air pollution in the United States. This created a dispute between Canada and the United States, then they agreed to settle it through a neutral arbitration court. As a result, this arbitration court ruling creates two principles of international environmental law primarily; the polluter pays the principle and obligation of the state not to damage the environment outside its jurisdiction. This arbitration award establishes the concept of Harm across borders and the principle of polluter pays to ensure the sovereignty of international environmental law. Therefore; if disputes arise between countries, they can resolve them through peaceful dispute resolution mechanisms such as negotiation, mediation and arbitration.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.032 | 0.005 |
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".