Placing and Displacing Science: Science and the Gates of Judicial Power in Environmental Cases
Bibliographic record
Abstract
Science and law are two dimensions of power that have a significant impact on people and places. Science and law often meet in cases brought before the courts, yet how courts react to scientific issues varies. In some instances, law seems to displace science, when courts treat cases as primarily legal disputes in which science plays a small role. In others, courts seem to allow science to displace judicial power, citing the complexity of science and the institutional incapacity or inappropriateness of courts to deal with these issues as a reason to decline to exercise judicial power. Why the differences? Are judges using scientific complexity or uncertainty as a tool for judicial gatekeeping? When courts define a particular issue as primarily scientific as opposed to primarily legal, what does this tell us about how courts understand the nature of different types of problems, and their own role in their resolution? What impact does this have on access to justice, and more particularly on access to the domain of legal power for those seeking to challenge, or obtain protection from, the dimension of scientific power? This paper contrasts judicial approaches to science in two legal contexts: the public law context of judicial review of environmental assessment decisions, and the private law context of toxic tort litigation. It also proposes examples of current innovations in overcoming these scientific barriers, and asks what these innovations reveal about evolving judicial attitudes toward the relative place of science and law in resolving environmental problems.
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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 | 0.055 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.022 | 0.107 |
| Scholarly communication | 0.031 | 0.029 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.018 | 0.013 |
| 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".