Risky Politics: A Sociological Analysis of the WTO Panel on Biotechnological Products
Bibliographic record
Abstract
The above quotes illustrate the international conflict within the World Trade Organization over the definition of risks from GM foods.2 Canada and Argentina challenged the emphasis of the European Communities, now the European Union, on the existence of risks associated with these products. Together with the United States of America (USA), these countries are the complaining Parties to this trade dispute. In their view, GM products are not an issue of risk. The trade conflict can be recast as a struggle for definitions, or more precisely a conflict as to how to circumscribe the issue of genetically modified agricultural products in between the logics of politics, economy and science. In the above citations, Canada was contesting the European policy for GMOs and situated the framework of the problem at the frontiers of the economy when referring to modern agriculture, while Argentina highlighted the scientific discussion of risk. The European position was portrayed as dealing with the risks within the political realm of its GMO policy. All sides rely on science to support their arguments, one emphasizing its accomplishments to ensure the safety of biotechnological products and the other focusing on its limits in the face of uncertainty.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".