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Record W4246267805 · doi:10.1163/1573035053683263

Objects of Private Property in the Civil Code of the Russian Federation and in the Civil Code of Quebec

2005· article· en· W4246267805 on OpenAlexaboutno aff
David Lametti

Bibliographic record

VenueReview of Central and East European Law · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsCivil codeProperty (philosophy)Tangible propertyCode (set theory)Context (archaeology)Object (grammar)Political scienceCLARITYIntangible propertyLaw and economicsProperty rightsPrivate propertyImmovable propertyLawSociologySet (abstract data type)Computer scienceEpistemologyGeographyPhilosophyArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

Abstract Property norms, in expressing a relationship among people through resources, must address in some manner the organization of property rights and the classification of objects of property. Both the Civil Code of the Russian Federation and the Civil Code of Quebec express some notion of the idea of what the author has called property-as-object, taking the form of certain distinctions: movable/immovable, corporeal/incorporeal, capital/revenue, or in commerce/out of commerce.The Russian code contains a rich discussion of the objects of property, with a larger, more explicit formal role for objects in the understanding of property rights as compared to the Quebec code. The articles on objects in general manifest the traditional civilist distinctions, while set in the context of present Russian society.Moreover, notwithstanding some initial lack of clarity in the Russian code's classifi cation between the objects of property and the subject-matter of other patrimonial rights, the objects of property are clearly distinguishable as a category and are important to understanding property relations. Despite the focus in the Russian code on "things" as the objects of property as opposed to "rights in things", it is nevertheless the case that the latter are an important part of the property relationship, and cannot be disentangled from "things".

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0030.010
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.200
Teacher spread0.185 · 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
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
Published2005
Admission routes1
Has abstractyes

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