The State as Polluter Challenge in Climate Law
Bibliographic record
Abstract
It is commonly assumed that private actors cause climate change. This assumption problematizes international environmental law and suggests that the conduct of private actors should be the principal focus of climate law. This thesis challenges the empirical predicate and legal implications of this common assumption. The assumption is empirically wrong because states-controlled polluters are responsible for much of the global greenhouse gas emissions. The assumption is also legally misleading because it obscures a state’s obligations under international climate change law. Acknowledging the state’s direct contributions to climate change and its attendant legal consequences justifies litigation against states and their entities, or ‘state as polluter’ litigation. The trajectory of state as polluter litigation, however, will be shaped by the law of state attribution and the law of state immunity. These jurisdictional hurdles limit the scope —but do not foreclose — the possibility of state as polluter litigation before international and foreign tribunals.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| 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".