Development and climate change adaptation funding: coordination and integration
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.
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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 | 0.028 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 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".