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Record W3121452749

The Author as Agent of Information Policy: The Relationship between Economic and Moral Rights in Copyright

2008· article· en· W3121452749 on OpenAlexaff
Margaret Ann Wilkinson

Bibliographic record

VenueSSRN Electronic Journal · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsWestern University
Fundersnot available
KeywordsMoral rightsEnthusiasmScope (computer science)Law and economicsContext (archaeology)Function (biology)Political scienceBusinessEconomicsLawIntellectual propertySocial psychologyComputer sciencePsychology
DOInot available

Abstract

fetched live from OpenAlex

A historical and theoretical analysis of the copyright environment demonstrates that both the economic rights associated with copyright and the moral rights often associated with copyright perform social functions. The latter have not been as universally embraced or adopted as the former. The lack of enthusiasm for moral rights is argued to be because the social utility of this aspect of the copyright regime has gone largely unrecognised. In fact, moral rights ensure that the information needs of the public are being met because they enhance the ability to assess the authority and reliability of information. While historically this has not been as important as enhancing the supply of information, a function performed by the economic rights of copyright, in the context of the new information environment, the role played by moral rights is becoming increasingly important. Our thesis also defines the appropriate scope of moral rights protection in 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 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)0.012
metaresearch head score (Gemma)0.047
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 score0.016
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.022
Scholarly communication0.0160.018
Open science0.0010.003
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.032
GPT teacher head0.247
Teacher spread0.215 · 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
Published2008
Admission routes1
Has abstractyes

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