Managing Trade in Products of Biotechnology—Which Alternative to Choose: Science or Politics?
Bibliographic record
Abstract
Biotechnology has triggered a spirited debate about how to assess risks, what rules to use, and where to vest the authority to decide. Post World War II, there has been a strong move to normalize and institutionalize a 'science-informed' system in international science and trade treaties. Recently there has been a pushback against the privileged role science institutions play in decision-making, especially regarding genetically modified crops. Some countries have tried to use legal derogations in institutions such as the World Trade Organization, while others have attempted to construct and implement competing power systems, mostly revolving around the Convention on Biological Diversity to supplement or replace science-informed decision-making with socio-economic considerations. Neither effort has been entirely satisfactory. The Americas generally follow the science-based regulatory framework, while Europe and Africa at times pursue a socio-economic-based regulatory framework. We assess the underlying information, valuation, and selection rules involved in the battle between 'science-informed' decision-making and rules incorporating socio-economic considerations in global agri-food trade, concluding that a generally accepted comprehensive approach to the regulation of products of biotechnology is unlikely in the foreseeable future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".