Piecemeal Transparency: An Appraisal of Regulation (EU) No. 2019/1381 on the Transparency and Sustainability of the EU Risk Assessment in the Food Chain
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
For some time, pressure was placed on the European Food Safety Authority concerning the manner in which it conducted risk assessments in relation to food safety. This pressure culminated in the introduction of Regulation (EU) No. 2019/1381 as the upshot to the European Citizens’ Initiative on glyphosate. Concerns were expressed in the initiative regarding the transparency of the scientific studies used to evaluate pesticides, and following a Fitness Check conducted by the European Commission. Effectively, the new Regulation seeks to impose an obligation on EFSA to publish industry studies at the beginning of the risk assessment process. However, the mandatory nature of this obligation raises a number of concerns as to whether the urge to increase the transparency of the work of the EU authorities is more important than keeping the research confidential, two converse ideals in the realm of European law and effective processes. The present article submits that this codified focus on the risk assessment process and its accessibility for European citizens is a new frontier for transparency within the EU risk assessment processes. Yet while the changes pioneered by this framework are laudable, the Regulation is not without its qualifications.
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.
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 | 0.002 | 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) | 0.000 | 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