Empowering International Law to Address Claims for Climate Reparations
Bibliographic record
Abstract
A fundamental and widely recognized inequity at the core of the existential climate crisis facing the planet today is that those who have contributed the least to climate change are also the most affected. The United States, European Union-28, Russia, Japan, and Canada, according to some accounts, are together responsible for 85 percent of global greenhouse gases (GHG) emissions thus far.1 Yet it is the climate vulnerable—least developed countries, low lying, and small island states among others—that are at the frontlines of climate impacts. There is widespread scientific and diplomatic consensus on the multiple causes and devastating impacts of climate change but so far justice for vulnerable states has proven elusive.
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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 | 0.048 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.021 | 0.021 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.040 | 0.030 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".