EU Environmental Principles and Scientific Uncertainty before National Courts
Bibliographic record
Abstract
This comparative book explores the dynamics driving how courts across Europe and beyond understand and analyse scientific information in nature conservation. The Habitats and the Birds Directives – the core of EU nature conservation law – are usually seen as the most ‘uniform’ parts of EU environmental law. This book analyses the case law from 11 current and former EU Member States’ courts and explores the dynamics of how, and crucially why, their understandings of scientific uncertainty on the one hand, and EU environmental principles on the other, vary. The courts’ scope and depth of review, access to scientific knowledge, and scientific literacy all influence such decisions – as does their interpretation of norms and principles. How have the courts evaluated scientific evidence, encompassing its essential uncertainties? This book answers this and many more questions pertinent to EU environmental law, comparative environmental law, administrative law, and STS studies. Co-edited by
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".