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Record W2229243899 · doi:10.1017/cbo9781139505994.013

The framing of a European law of trusts

2013· book-chapter· en· W2229243899 on OpenAlexaff
Alexandra Braun

Bibliographic record

VenueCambridge University Press eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsFraming (construction)LawPolitical scienceLaw and economicsSociologyGeography

Abstract

fetched live from OpenAlex

Since the Hague Convention on the Law Applicable to Trusts and on their Recognition came into force in 1992, trust law within the European Union has undergone a fascinating evolution. Some European legislatures have reformed already existing trust instruments, while others have introduced new domestic devices aimed at rendering their financial markets more competitive. As a consequence, the list of fiduciary instruments available within Europe has increased. This development has been seen by some as an obstacle to the free movement of capital and services as well as the mutual recognition, and it has been suggested that trust law should be rendered uniform within Europe. In 2009, the outcomes of two academic research projects were published suggesting that uniform instruments be introduced in the European Union. Although the aim and the scope of the two projects are inherently different, they both suggest a uniform fiduciary device for Europe. It would thus seem that the Hague Trusts Convention aimed at harmonizing trust law at the level of conflict of laws, has ultimately prepared the ground for proposals envisaging the harmonization of trust law at a substantive level. But is there a need for a European law of trusts? Do we have enough evidence to support such a claim and, if so, is the time ripe for an intervention of the European legislature? This chapter addresses these questions by taking a closer look both at the events that have occurred within Europe in the aftermath of the coming into force of the Hague Trusts Convention, and at the nature and essential features of the instruments propounded. In doing so it examines both the feasibility of the two instruments, as well as the need for a unification of this area of the law.

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)0.022
metaresearch head score (Gemma)0.027
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 score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.035
Scholarly communication0.0200.017
Open science0.0020.009
Research integrity0.0140.012
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.227
Teacher spread0.200 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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