MétaCan
Menu
Back to cohort
Record W2561205694

ANALYSIS OF THE RELATION OF COPYRIGHT AND WORK CONTENT IN JUDICIAL VERDICTS OF USA, UK AND CANADA

2015· article· en· W2561205694 on OpenAlexaboutno aff
mahmoud sadeghi, Sara Allameh

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsRelation (database)Work (physics)Content (measure theory)LawPolitical scienceEngineeringComputer scienceMathematicsDatabase
DOInot available

Abstract

fetched live from OpenAlex

According to copyright system, the normal standard for protecting literary and artistic works is originality hence the international copyright treaties such as Berne convention, while emphasizing on originality are avoiding imposing other mandatory standards for protecting such works. However, these works are different forms of expression of various ideas and accordingly, comprise different contents. In some cases, the works contents are inconsistent with religious and national values and norms or society custom and laws. There are conflicts between protecting copyright as an intellectual property right and other moral, religious and legal priorities in the society. For resolving this conflict and answering the question whether work content will affect copyright protection, countries have adopted different approaches. From the perspective of the work content, this article through a comparative study of approaches and judicial verdicts of the USA, the UK and Canada, infers two general views: the work content does not have any impacts on copyright protection and the work content have impacts on copyright protection. In addition, some supporters of second view believe in content impact on existence of copyright in a work and other supporters believe that content has impacts on some enforcements of copyright.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.283
GPT teacher head0.452
Teacher spread0.169 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicLaw, AI, and Intellectual PropertyFrench-language works237,207