Public International Funding of Nature-based Solutions for Adaptation: A Landscape Assessment
Bibliographic record
Abstract
This paper provides the first assessment of the landscape of public international funding for nature-based solutions for climate adaptation, covering both climate finance and Official Development Assistance (ODA). It seeks to help donor countries, multilateral institutions, and developing countries better understand the current state of funding, and provides recommendations to address barriers that are hindering public donor funding support for nature-based solutions for adaptation. The Global Commission on Adaptation's 2019 flagship report Adapt Now: A Global Call for Leadership on Climate Resilience identified access to finance as one of three key barriers that impede the scaling up of nature-based solutions for adaptation in many countries. This paper shows that the amount of public international funding flowing to nature-based solutions (NbS) for adaptation in developing countries is still relatively small. This paper was produced by World Resources Institute and Climate Finance Advisors in support of the Global Commission on Adaptation.
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".