Transatlantic Differences in GMO Regulation
Bibliographic record
Abstract
A Case Study ApproachWhen it comes to GMOs the European Union (EU) and the United States (US) have chosen strictly opposing paths, although they were confronted with the same questions and information surrounding the GMO debate. With the statement above, Dan Glickman,the former United States Secretary of Agriculture, expressed his concern about the state of public opinion on biotechnology in Europe. It is a nice illustration of some of the differences and stereotypes surrounding the topic of genetically modified organisms (GMOs): whereas, for instance, the European regulatory system is generally characterised as politicised, decentralised and precautionary, the US system is often said to be the complete opposite, namely technocratic, centralised and sound science-based.The strikingly different regulatory approaches towards GMOs have created an international debate regarding the production, cultivation and consumption of food made from or with GMOs. The different regulatory approaches employed by the EU and the US “created serious obstacles to the export of agricultural products from the United States, and in turn raised the prospect of a major international trade war over the approval and marketing of GM foods and crops” (Shaffer, 2004, p. 2). In 2003, the conflict culminated in a World Trade Organization (WTO) case filed by the US, Canada and Argentina against the EU. Inter alia, the complainants challenged the unofficial de facto moratorium of the EU on the approval of biotech products and the national safeguard measures adopted by certain Member States (WTO, 2010). In 2006, the WTO ruled that the EU was indeed breaching its obligations under the WTO Agreement on the Application of Sanitary and Phytosanitary Measures (SPS Agreement). The regulatory differences in GMO regulation between the EU and the US have triggered a debate which has attracted the attention of scholars from various different disciplines and academic backgrounds. Jasanoff, for example, uses the concept of political culture to show that the different approaches taken by the EU and the US reflect “more or less self-conscious projects of nation-building” (Jasanoff, 2007, p.7). Vogel, by contrast, examines the regulatory differences from a political scientist´s perspective proposing three interrelated factors – the intensity of public pressure, the political preference of influential policy makers, and the criteria used for risk assessment – in order to account for the transatlantic regulatory divergence of GMOs (Vogel, 2012). Also jurists like Wiener and Alemanno have engaged in the topic focusing inter alia on the application of the precautionary principle in the EU and the US, or the role of the WTO (Wiener J.B., Rogers, M.B., Hammit, J.K., Sand, P.H., 2011; Alemanno, 2010).
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".