Bibliographic record
Abstract
Part one. Introduction. Historical background -- A Canadian law of restitution -- General principles -- Part two. Remedies. Common law remedies -- Equitable remedies -- Tracing at law -- Tracing in equity -- Subrogation -- Contribution and indemnity -- Part three. The right to restitution. Topic I. Mistake. Money paid under a mistake of fact -- Money paid under a mistake of law -- Other benefits conferred by mistake -- Topic II. Ineffective transactions. Informality -- Incapacity -- Illegality -- Want of authority -- Mistake, misunderstanding and uncertainty -- Frustration -- Discharge for breach -- Misrepresentation -- Contracts and gifts which do not materialize -- Topic III. Public authorities. Restitution from public authorities -- Topic IV. Profit from wrongdoing. Criminal and quasi-criminal acts -- Waiver of tort -- Breach of contract -- Compulsion -- Breach of fiduciary duty -- Breach of confidence -- Unconscionable transactions -- Other equitable wrongdoing -- Topic V. Officiousness. Necessitous intervention : the altruistic intermeddler -- Compulsory discharge of another's liability -- The self-serving intermeddler -- Topic VI. Pettkus v. Becker and its progeny. Property disputes between cohabitants -- Topic VII. Benefits acquired from third parties. Restitution of benefits conferred upon the defendant by a third party -- Benefits wrongly acquired by a third party before transfer to the defendant.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 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".