Biodiversity and Development Finance 2015-2021
Bibliographic record
Abstract
This report provides an overview of the main trends of annual development finance with biodiversity-related objectives for the period 2015 to 2021, from a range of sources: bilateral Development Assistance Committee (DAC) members and non-DAC members, South-South and triangular co-operation providers, multilateral development banks (MDBs) and other multilateral institutions, private finance mobilised by development finance, and private philanthropy. The estimates are based on OECD statistical data, capturing both official development assistance (ODA) and non-concessional development finance. It includes breakdowns by biodiversity-related providers, sectors, financial instruments, recipient country groupings, and on the biodiversity and climate change nexus. These elements can help DAC members and other stakeholders to step up and target their biodiversity-related investments, notably to implement the Kunming-Montreal Global Biodiversity Framework under the Convention on Biological Diversity and track progress against its Target 19(a) on resources mobilisation. The findings in this report draw from the OECD publication A Decade of Development Finance for Biodiversity: 2011-2020.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".