Bibliographic record
Abstract
The public nuisance tort is now in a critical stage of development, mostly in the United States but also in other jurisdictions, including civil law systems. It is becoming ever more consequential in practice and, at the same time, widely misunderstood by courts and scholars. Our ambition is to defend a private law theory of public nuisance. Contrary to the view that the underlying rights protected by this tort contrast with private rights (say, to bodily integrity), we argue that these public rights are private rights like any other right in the law of torts since they protect private persons taken severally. And, yet, these private rights are also distinctively public in the sense that they protect the interests of private persons to use and enjoy the public sphere. In that, public nuisance imposes not merely ex post liability for undermining these interests but also, first and foremost, constructs a liberal public sphere. Our case for public nuisance shows that private law extends beyond the private sphere to capture entitlements and responsibilities that do not arise from, or attach to, ownership of land; it also resists the reduction of private law to rights of action and ex post determination of liabilities. More concretely, our reconstruction of public nuisance solves two key doctrinal challenges that the tort struggles with – concerning the standing to sue in public nuisance and the economic loss rule – and it also refines the potentially significant role of this tort in addressing the urgent threat posed by climate change.
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.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".