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Record W2261148905

Characterization of Proprietary Restitution in the Conflict of Laws

2012· article· en· W2261148905 on OpenAlexaff
Pattarapas Tudsri

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsRestitutionUnjust enrichmentPrivate lawLawConstructive trustConflict of lawsMunicipal lawWrongdoingCommon lawPolitical sciencePublic lawPhilosophy of lawInternational lawComparative lawLaw and economicsSociology
DOInot available

Abstract

fetched live from OpenAlex

This article examines the interaction of the law of restitution for unjust enrichment and the law of property with private international law. Classically, in private international law, the first step in the analysis of the governing law of a dispute with international elements is the classification of the dispute. This classification process sometimes involves much complexity, and this has been the case particularly for claims which in the domestic common law have been described as “proprietary restitution”.This article begins by examining many of the critical, long-lasting debates concerning the domestic law organization of the concepts of restitution and unjust enrichment, with particular regards to pro- prietary restitutionary remedies which may arise in connection with claims said to be based on unjust enrichment. When turning to private international law, the author seeks to develop an approach that attempts to go beyond the internal debates on classification and to arrive at a more neutral approach of classification that is likely to work well with the choice of law rules which have been developed essentially in accordance with the civilian, as opposed to the common law, categories of causes of action. In analyzing the classification process at the private international law level, the author attempts to address all of the major domestic law proprietary restitutionary claims such as claims to traceable proceeds, proprietary claims to the profits of wrongdoing, resulting trusts, constructive trusts arising in mistaken transfers and remedial constructive trusts.

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)0.006
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0050.029
Scholarly communication0.0100.015
Open science0.0020.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.031
GPT teacher head0.312
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

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