Legally binding and ambitious biodiversity protection under the CBD, the global biodiversity framework, and human rights law
Bibliographic record
Abstract
Abstract Beyond climate change, the planet faces several other environmental challenges that are at least as threatening, such as the loss of biodiversity. In each case, the problems are driven by similar factors, such as fossil fuels and intensive livestock farming. This paper presents a legal analysis concerning the binding nature of the Convention on Biological Diversity’s (CBD) overarching objective to halt biodiversity loss, within the framework of international environmental and human rights law. Using the established legal techniques encompassing grammatical, systematic, teleological, and historical interpretations, the article demonstrates that the CBD’s objective to halt biodiversity loss is indeed legally binding and justiciable. This conclusion is directly drawn from interpreting Article 1 CBD. Furthermore, a comparable obligation emerges indirectly from international climate law. The imperative to curtail biodiversity loss also finds grounding in human rights law, albeit necessitating a re-evaluation of certain aspects of freedom, similar to what has been explored in the context of climate protection. Moreover, the article underscores that various other biodiversity-related regulations within international law, including those laid out in the CBD, the Aichi Targets, and the Kunming–Montreal Global Biodiversity Framework, also carry partial legal significance. Nonetheless, it is crucial to note that these regulations, including the Kunming–Montreal Framework, do not modify the obligation mandate to halt biodiversity loss, which was established at the latest when the CBD entered into force in 1993. Because this obligation has been violated since then, states could potentially be subject to legal action before international or domestic courts for their actions or inactions contributing to global 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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.043 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".