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Record W2271061355 · doi:10.1515/bjes-2015-0017

The Last Habitual Residence of the Deceased as the Principal Connecting Factor in the Context of the Succession Regulation (650/2012)

2015· article· en· W2271061355 on OpenAlexfundno aff
Max Atallah

Bibliographic record

VenueBaltic Journal of European Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicConflict of Laws and Jurisdiction
Canadian institutionsnot available
FundersDirectorate-General for JusticeEuropean CommissionTallinna TehnikaülikoolUniversity of GlasgowInstitute for Catastrophic Loss ReductionEmory University
KeywordsContext (archaeology)Principal (computer security)JurisprudenceResidenceBachelorLegal certaintyEcological successionCertaintyMember statePolitical scienceLawMember statesSubject (documents)Law and economicsSociologyEuropean unionBusinessComputer scienceGeographyComputer securityMathematicsDemography

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to gather information about the last habitual residence (LHR) of the deceased in the context of the upcoming EU Succession Regulation. In addition, the aim was to analyze the adequacy of the legally undefined LHR as the principal connecting factor in cross-border succession within the EU. This study was carried out as a part of a bachelor thesis conducted on the same subject. The data were collected from relevant jurisprudence, international law, national acts, the EU published materials and case law. These results suggest that the legally undefined LHR is an unstable connecting factor for the purposes of the Succession Regulation, since it cannot guarantee sufficient legal certainty, and hence, the EU citizens are not able to fully utilize their right to free movement. The findings indicate that there might be a need to amend a legal definition for the LHR, not only for the EU Member States to be able to apply the concept in an harmonized way, but also for the EU citizens to know whether they are considered habitually resident in a state or not.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.352
Teacher spread0.271 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2015
Admission routes1
Has abstractyes

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