COP 15 - Can We Meet Biodiversity Goals & Targets?
Bibliographic record
Abstract
The 15th Conference of Parties (COP15) for the UN Convention on Biological Diversity was held in two parts (in Kunming, China, in October 2021 and in Montreal, Canada, in December 2022). One primary goal for COP15 was the development of a Global Biodiversity Framework (GBF) covering the coming decade (from 2023 through 2030). The GBF produced by the participating countries at COP15 included four long-term global goals for 2050 linked to the 2050 Vision for Biodiversity, along with 23 global targets for immediate action and completed by 2030. One outcome of the negotiations was the identification of the need to increase public awareness of the global biodiversity crisis leading to sustained activities to halt and reverse global biodiversity loss.
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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.072 | 0.024 |
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".