Public International Funding of Nature-based Solutions for Adaptation: A Landscape Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it