An analysis of the Kunming-Montreal Global Biodiversity Framework
Bibliographic record
Abstract
Biodiversity is a fundamental precondition for a healthy environment and therefore an indispensable prerequisite for human life. There have already been many mass extinctions of species and ecosystems in the history of the Earth, however, as the human way of life is severely affecting the environment including biodiversity another one is feared. Legal instruments such as multilateral environmental agreements can support biodiversity protection worldwide. \nThe most important agreement in this respect is the Convention on Biological Diversity. The Convention´s Conference of the Parties is the body that adopts global biodiversity targets. In this context, the importance of the Conference of the Parties must be emphasized, especially since its decisions, although not legally binding in principle, are of decisive importance for the interpretation of the Convention and aims to operationalise its objectives. \nUnfortunately, not all the of the global biodiversity targets of the Strategic Plan 2011–2020 (Aichi targets) were achieved at a global level. Due to this, in December 2022, the 15th Conference of the Parties adopted new biodiversity targets as part of the Kunming-Montreal Global Biodiversity Framework (Kunming-Montreal targets). The objective of this thesis is to compare the both, highlight important innovations introduced by the Kunming-Montreal Global Biodiversity Framework and how it is currently being implemented at international, regional, and national level. In addition, this thesis analyses and explains which Aichi targets were partially achieved and which were not. \nFinally, the effectiveness of the Convention must also be viewed critically, in particular the lack of a functioning compliance mechanism. This is just as much a problem as the unclear legal effect of the decisions of the Conference of the Parties. There are other aspects that could lead to an improvement in the efficiency of both the Convention and the Kunming-Montreal Global Biodiversity Framework. Some issues include the discussion about the United States accession to the Convention on Biological Diversity, a privatisation of natural resources, and the question of whether the Security Council should address the issue of biodiversity loss.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".