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NATIONAL MECHANISMS OF REGULATION OF CROSS-BORDER COPYRIGHT RELATIONS AIMED AT PROTECTION OF ORPHAN WORKS

2019· article· en· W2992382027 on OpenAlexaboutno aff
Г К Дмитриева, Оксана Луткова

Bibliographic record

VenueLex Russica · 2019
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsPermissionPolitical scienceLaw and economicsLawDigitizationSociologyEngineeringTelecommunications

Abstract

fetched live from OpenAlex

The article has investigated the mechanisms of the national (both legal and non-legal) regulation of orphan works, i.e. works the holder (holders) of rights to which is (are) not identified and/or the location of the rights-holder is not established. Orphan works are supposedly protected by copyright, which means the validity of exclusive rights and the potential need to obtain permission from the copyright holder for any form of using the works under consideration, namely: reproduction including digitization, translation, processing, etc. However, in a situation where the right holder is not determined (is unavailable), the user does not have an objective opportunity to obtain such a permission, and the work actually remains unknown to the society, although it can be of artistic, cultural or historical value. Since the beginning of the new millennium, the national legal systems of a number of States have establish a special regime for the legal protection of orphan works, and about 20 states of the world have developed the foundations of such a regime so far. The article analyzes the regulation of orphan works in several states — in the EU and its member states, Great Britain, the USA, Canada, Korea, Japan, India. The authors have determined the foundations of the substantive and conflict of laws regulation of cross-border relations regulating orphan works. Features of regulation of works with an unidentified author in the era of a network society are highlighted: in particular, the need to digitize orphan works, since many of them are in a single copy on the medium ruined by time, and the fact that the digitized work can instantly spread from databases to other jurisdictions. The authors provide for the forecast of possible ways of evolution of legal regulation of relations in question with the use of mechanisms of national and international 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)0.010
metaresearch head score (Gemma)0.014
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 score0.011
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0040.014
Scholarly communication0.0110.005
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.016
GPT teacher head0.284
Teacher spread0.267 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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