Development and climate change adaptation funding: coordination and integration
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
Within a few decades, tens of billions, and possibly over a hundred billion, dollars will be needed for climate change adaptation in developing countries. In recent international climate negotiations, US$100 billion per year by 2020 was pledged by developed countries for mitigation and adaptation. Even if this pledge is realized, it is not clear that it will generate sufficient funds to address the adaptation needs of developing countries. A majority of what has been identified as climate change adaptation needs could be considered as funding for basic development. In addition, a large share of current development assistance is spent on climate-sensitive projects. With the potential for funding of climate change adaptation to fall short of what is needed and for development funding to continue funding many climate-sensitive activities, coordination of the two funding streams may enable more effective support for both sustainable development and climate change adaptation. Preliminary steps to facilitate such coordination are part of the Cancun Agreements and initiatives by other organizations.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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