Victim Pays Damages to Tortfeasor: The When and Wherefore
Bibliographic record
Abstract
Is there a reality in which the victim pays damages to the tortfeasor? This article analyzes Calabresi and Melamed’s liability rule for the damaging party (Rule 4), where the damaged party has the right to prevent pollution if the polluter is compensated first. Under the conventional application of this rule, the victim first collects the money and compensates the injurer, and only then is the injurer required to eliminate the nuisance (ex ante). There is no reference to a possibility of the injurer first eliminating the nuisance and only then receiving compensation (ex post). We argue that the timing of the payment should be changed when the activity causing the nuisance has social and economic value. Each version of the rule advances the aggregate welfare in some sense, but also harms it in another. The primary aim of the present article is to introduce a new model for Rule 4 that would guide legislators, regulators, and judges in deciding when to order compensation as a condition for eliminating the nuisance and when to order the injurer to remove the nuisance first and only then collect the funds. This article also introduces a comparative perspective that reveals the potential use of the ex post version of Rule 4, as manifest in sources of the Jewish legal tradition. This comparison further bolsters our proposal in favour of a division between ex ante and ex post versions of the rule. Ultimately, offering two versions for the implementation of Rule 4 would better enable the adaptation of a suitable solution according to the circumstances and thus would widen the possibilities for the rule’s use.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".