International biodiversity finance: Reframing payments for ecosystem services within a co-investment for sustainable development approach
Bibliographic record
Abstract
Financing nature-positive development pathways in Southern countries is a central issue in the implementation of the Global Biodiversity Framework adopted in Montreal at COP15, and links to two streams: the need expressed by Southern countries to receive support for biodiversity protection through public finance from Northern countries; and the issue of aligning all financial flows with biodiversity objectives. Both issues emphasize “innovative finance mechanisms”, and in particular framing some of these flows, public or private, as “payments for ecosystem services”. This Issue Brief repositions “payments for environmental services” schemes within a broader approach of co-investment for sustainable development. After examining the gap in investments for development in low income and lower middle-income countries, and the role and place of biodiversity in their development pathways, the paper discusses the nature of services provided by biodiversity and how they can be linked to payments, before looking at other financial sources that could contribute to a co-investment approach.
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.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".