The Responsibility of States Regarding Climate Change: International Cooperation to Reduce Toxic Emissions that Harm the Atmosphere
Bibliographic record
Abstract
Carbon dioxide emissions from the usage of fossil fuels contribute to anthropogenic climate change.The Climate Change International Legal Regime, which consists of primary principles outlined in international treaties, was designed to minimize greenhouse gas emissions.According to customary international law, governments are prohibited from causing harm to one other.A nation breaches this principle when an action within its jurisdiction causes harm to another nation, either intentionally or as a result of negligence.With limited efforts to address climate change, there is a significant likelihood that the damages caused by climate change would escalate in terms of quantity, intensity, and frequency.Amidst the era of climate change, it is imperative for States to take resolute action.Nevertheless, it is disheartening to observe the absence of aggressive endeavors in climate treaty discussions, which is manifested in the vague character of non-binding or lenient mitigation commitments.From this perspective, this paper contends that courts have the potential to act as catalysts for change and exert pressure on States, albeit with some caution, to implement decisive measures.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".