Loss and Damage from climate change: legacies from Glasgow and Sharm el-Sheikh
Bibliographic record
Abstract
Conferences of the UN climate change convention have legacies both in formal outcomes and treaties and in raising the profile of emerging climate dilemmas. The joint legacies of COP26 in Glasgow and COP27 in Sharm el-Sheikh have been in elevating the profile and formalising the potential for solidaristic action on ‘Loss and Damage’ from climate change. This article reviews the documented outcomes on Loss and Damage from the two events to analyse the significance and constraints of this element of the overall climate change regime. Loss and Damage is likely to be constrained as a global collective action by the capacity to identify and measure losses and damages and by the ability of the climate change regime to deliver on meaningful resource transfers. Yet the formalisation of elements of climate justice through Loss and Damage is a real and lasting legacy of these COP events.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| 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".