Socio‐economic Considerations in Biosafety and Biotechnology Decision Making: The Cartagena Protocol and National Biosafety Frameworks
Bibliographic record
Abstract
Abstract Article 26.1 of the Cartagena Protocol on Biosafety left open the possibility for member countries to include in their biosafety regulatory processes the assessment of socio‐economic considerations. Countries may also decide to include such assessments as part of their national legislation or regulations for the approval and deliberate release into the environment of genetically engineered technologies. Countries are debating if and how to implement assessment of socio‐economic considerations. This paper contributes to the ongoing policy dialogue by discussing issues related to socio‐economic assessment including scope, timing, inclusion modalities, methods, decision‐making rules and standards, and the integration of socio‐economic assessments in biosafety and/or biotechnology approval processes. This paper also discusses the implications of such inclusion for technology flows and public and private sector R&D. If inclusion is not done properly, it may negatively impact technology flows especially from the public sector and render an unworkable biosafety system.
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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 | 0.243 | 0.201 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.023 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".