Insurance between Neighbours: Stannard v Gore and Common Law Liability for Fire
Bibliographic record
Abstract
Liability under Rylands v Fletcher has since its inception been justified by ideas of risk-creation and loss-spreading, in circumstances where parties are free from blame. Pollock described it as amounting to an ‘insurance’ between neighbours; in its contrast with negligence liability, it has more recently been described as the ‘conscience’ of the law. Here we are concerned with the nature and limited existence of Rylands liability for damage done by the escape of fire after the Court of Appeal s decision in Stannard v Gore. How does ‘insurance’ through liability compare with the well-recognised and widespread practice in relation to fire, of insuring oneself? We particularly discuss the possible purposes of the long disembodied section 86 of the Fires Prevention (Metropolis) Act 1774, the significance of insurance in that statute, and the importance of rival interpretations of its applicability to Rylands liability. We identify the current difficulties in this area of law as lying in the elusiveness of the social purposes which have shaped its principles, suggesting that any justification of Rylands liability for fire should indeed take account of the long-established practice of first party insurance.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".