International synthetic biology policy developments and implications for global biodiversity goals
Bibliographic record
Abstract
In December 2022, the governments of 196 countries adopted the Kunming-Montreal Global Biodiversity Framework (KMGBF), a strategic plan to support and advance implementation of the objectives of the Convention on Biological Diversity (CBD) and its subsidiary agreements, including the Cartagena Protocol on Biosafety (Protocol). The KMGBF includes a “biosafety” target (Target 17), that reflects the CBD obligations for Parties to implement biosafety measures, and measures for handling biotechnology and distributing its benefits. The unprecedented inclusion of a biosafety target in the KMGBF, with explicit recognition of benefits and its placement amongst other targets for “tools and solutions for implementation and mainstreaming”, has ignited hope for renewed recognition of the potential for biotechnology to contribute to global environmental goals. This would mark a shift in this international forum that began with these intentions, but subsequently changed focus towards the potential adverse impacts of biotechnology and restrictive application of precaution. Simultaneously, a decade-long program of work on “synthetic biology” has been examining the implications of new developments in biotechnologies for the objectives of the CBD, with an emphasis on the scope and adequacy of existing biosafety measures, and more recently, “horizon scanning” for new technological developments. This review provides an overview of the status of biotechnology/synthetic biology policy developments under the CBD, focusing on the period from the drafting of the KMGBF in 2018 to current programs of work resulting from decisions made at the 2024 United Nations Biodiversity Conference. These are expected to have implications for biotechnology/synthetic biology capacity development and adoption, and implementation of the KMGBF. Relevant parallel policy developments under other international fora, including the International Union for the Conservation of Nature and Natural Resources (IUCN) and the Organisation for Economic Cooperation and Development (OECD), are also examined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".