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Record W6983587945

Moral Rights: The Future of Copyright?

2009· article· en· W6983587945 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2009
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
Fundersnot available
KeywordsMoral rightsIntellectual propertyHuman rightsInternational human rights lawFundamental rightsReservation of rightsRight to property
DOInot available

Abstract

fetched live from OpenAlex

August 20, 2009 Speaker: Mira T. Sundara Rajan, DPhil (Oxon) Canada Research Chair in Intellectual Property Law Associate Professor of Law University of British Columbia Presented by: Frederick K. Cox International Law Center Summary: This lecture will introduce the concept of the moral rights of the author, a special branch of copyright law dealing with the artistic, personal, and cultural interests implicated in copyright works. The session will seek to familiarize authors with the approach to moral rights in the United States and major international jurisdictions, including the European Union and United Kingdom, Canada, and India. Moral rights are an area of growing international importance, and there is a strong probability that moral rights claims and concerns will become increasingly common in an era of expanding digital technology. This seminar will help lawyers to identify moral rights issues in their practices, and to present effective arguments on moral rights claims, based on national and international copyright laws.

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)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.028
Scholarly communication0.0130.020
Open science0.0010.003
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0140.001

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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
Published2009
Admission routes1
Has abstractyes

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