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Record W7155367086 · doi:10.60082/2817-5069.3936

Is Illegality a Defence to Restitutionary Claims?

2025· article· en· W7155367086 on OpenAlexaffvenueabout
John D. McCamus

Bibliographic record

VenueOsgoode Hall law journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsYork University
Fundersnot available
KeywordsRestitutionPlaintiffDoctrinePresumptionUnjust enrichmentSupreme courtJurisprudenceDamages

Abstract

fetched live from OpenAlex

The traditional English jurisprudence granting restitution of benefits conferred under agreements rendered unenforceable because of illegality was unsatisfactory. As a general principle, it held that there was a presumption against restitutionary relief for benefits conferred under such agreements (the Holman principle). This principle was subject to a series of exceptions granting relief to parties who were innocent of fault with respect to the illegal conduct or, at least, less at fault than the defendant. The main difficulty with this approach was that it denied relief in cases where, though the plaintiff was implicated to some extent in the illegality as a perpetrator or, at least, a participant in the illegal conduct, restitution appeared appropriate. The traditional Holman exceptions were stretched to accommodate such cases and collateral forms of relief developed. The resulting doctrine was both complex and unpredictable in its application. A modern approach emerged in American and, more recently, in Canadian and Australian law, of simply granting recovery to a guilty party who could establish that, in the particular circumstances, restitutionary relief was appropriate. A different approach to modernization of the doctrine has been recently adopted in English law. In its 2016 decision in Patel v Mirza, the Supreme Court of the United Kingdom appears to have adopted a reform scheme proposed by Professor Peter Birks. In essence, the Birksian scheme reverses the Holman principle and presumes that all plaintiffs are entitled to recover such benefits. The defendant, however, is entitled to raise a defence of illegality which will not invariably be available against perpetrators of the illegal conduct. This paper argues that the new English model is deeply flawed and ought not be adopted elsewhere. The modern American, Australian, and Canadian approach offers a more direct and sound solution to the problem.

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0080.073
Scholarly communication0.0140.022
Open science0.0040.010
Research integrity0.0250.017
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.036
GPT teacher head0.380
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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