Bibliographic record
Abstract
This chapter seeks to identify the different possible bases for a restitutionary claim where money has been paid pursuant to a transaction which it is later discovered was ultra vires one of the parties. One feature of the swaps litigation is that a number of different grounds of restitution were in play at various stages in the litigation. Five possible bases can be identified in the swaps cases: mistake of law, (total) failure of consideration, absence of consideration, the void nature of the contract and incapacity. The mistake of law bar was abrogated in Scotland by the momentous decision of an Inner House bench of five judges of the Court of Session in Morgan Guaranty Trust Company of New York v Lothian Regional Council. The decision in Morgan Guaranty must be seen in the context of the fall of the mistake of law bar in a number of jurisdictions: it had already fallen in Canada, Australia, and South Africa.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".