Developments in Foreseeability and Remoteness: The Limits of Contract Damages
Bibliographic record
Abstract
The leading case on remoteness of damages in contract law continues to be the 1854 decision of the Exchequer Court in Hadley v. Baxendale. The plaintiff, who operated a grist mill, agreed with the defendant, a nation-wide carrier, to carry a broken mill shaft to serve as a pattern for the manufacture of a new shaft. The carrier’s undue delay caused the mill to be stopped for longer than it would otherwise have been, and the mill-owner claimed compensation for the consequent loss of profits. The carrier was held not to be liable in the absence of knowledge of the probable consequences of the delay. In a well-known passage Baron Alderson said:Now we think the proper rule in such a case as the present is this: where two parties have made a contract which one of them has broken, the damages which the other party ought to receive in respect of such breach of contract should be such as may fairly and reasonably be considered either arising naturally, i.e., according to the usual course of things, from such breach of contract itself, or such as may reasonably be supposed to have been in the contemplation of both parties, at the time they made the contract, as the probable result of the breach of it.
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 | 0.025 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.051 |
| Scholarly communication | 0.016 | 0.029 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 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".