Regulating genetically modified food: Policy trajectories, political culture, and risk perceptions in the U.S., Canada, and EU
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines whether national differences in political culture add an explanatory dimension to the formulation of policy in the area of biotechnology, especially with respect to genetically modified food. The analysis links the formulation of protective regulatory policies governing genetically modified food to both country and region-specific differences in uncertainty tolerance levels and risk perceptions in the United States, Canada, and European Union. Based on polling data and document analysis, the findings illustrate that these differences matter. Following a mostly opportunistic risk perception within an environment of high tolerance for uncertainty, policymakers in the United States and Canada modified existing regulatory frameworks that govern genetically modified food in their respective countries. In contrast, the mostly cautious perception of new food technologies and low tolerance for uncertainty among European Union member states has contributed to the creation of elaborate and stringent regulatory policies governing genetically modified food.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it