The Role of Zoos and Aquariums in Contributing to the Kunming–Montreal Global Biodiversity Framework
Bibliographic record
Abstract
It is now well established that human-induced species extinctions and habitat degradation are currently occurring at unprecedented rates. To halt and reverse this decline, the international community adopted the Kunming–Montreal Global Biodiversity Framework (GBF), as part of the Kunming–Montreal Biodiversity Package, in December 2022. We clarify what this new framework means for conservation zoos and aquariums in their mission to prevent species extinction by highlighting areas of focus. We explain why it is necessary that conservation zoos and aquariums establish the appropriate mechanisms for contributing towards such a framework to help validate their role in the 21st Century. Conservation zoos and aquariums should be reassured that much of their work already fits within the GBF. However, the current mechanisms for individual zoos and aquariums to directly contribute to the implementation of the GBF mostly rely on close collaboration with individual national governments and/or are only possible at a national level. It is therefore critical that national, regional, and global zoo membership organisations take a leading role in championing the work of their members. Equally, adequately linking the efforts of zoos and aquariums to the national implementation of international instruments, such as the GBF, is imperative to ensure that these organizations’ contributions feed into the understanding we have of global progress towards the implementation of international instruments.
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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 | 0.024 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".