Agricultural Biotechnology and Regime Formation: A Constructivist Assessment of the Prospects
Bibliographic record
Abstract
Controversies surrounding the appropriate use and diffusion of agricultural biotechnologies are giving rise to questions about governance at the international level. This article investigates the likelihood that a single, international regime or multiple regimes governing this technology will form by way of negotiation. We show that four normative-institutional arrangements, organized around distinct general principles, have a potential governance role: world food security and safety, liberalized trade, protection of intellectual property, and conservation and sustainable use of biodiversity. We argue that an adequate amount of compatibility between the principles and norms of these arrangements is required to support the type of communicative action or truth-seeking needed to develop the intersubjective understanding for a regime. Using a framework for assessing normative compatibility, we find not one, but two nascent understandings rooted in the trade and biodiversity areas competing to form the foundation for governance. Further analysis of levels of institutional density between the two developing regimes reveals they are presently too low to support a negotiated resolution of normative conflict. Finally, we demonstrate that recent framing attempts at the international level to decrease areas of tension and incompatibility in principles/norms between the regimes have neglected to create the crucial normative background conditions needed to avert a scenario of increased political conflict in the near future.
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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 | 0.032 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".