Legal Systems and Loss & Damage at the Ocean-Climate Nexus: a Tribute to Meinhard Doelle
Bibliographic record
Abstract
Abstract In 2021, the Research Handbook on Climate Change Law and Loss & Damage was published. Co-edited by myself and my late colleague Meinhard Doelle, the Handbook seeks to clarify the need for legal systems, both within and beyond the climate regime, to evolve so as to fairly and equitably address climate loss and damage claims. The Handbook considers the challenges of legal remedy for climate loss & damage from the perspectives of public international law and domestic, transnational, and private international law. While loss & damage at the ocean-climate nexus is implicit in many chapters, this contribution will reflect explicitly on how the lessons from the Handbook could apply at the ocean-climate nexus, with reference to the London Convention and Stockholm Declaration at fifty, developments at COP 28, and the Advisory Opinion on Climate Change before the International Tribunal for the Law of the Sea.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".