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Record W7024018712

Of Pride and Prejudice: Mangled Art, Mutilated Statues, Hypersensitive Authors and the Moral Right of Integrity

2016· article· en· W7024018712 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsReputationHarmDoctrinePrejudice (legal term)PridePower (physics)Test (biology)Common law
DOInot available

Abstract

fetched live from OpenAlex

The issue of how much protection should be given to the so-called ‘moral rights’ of artists has intrigued and engaged scholars and policymakers for decades. Although the moral right of integrity seeks to protect an artist’s work from ‘derogatory treatment’, there is no universal consensus on the standard by which ‘derogatory’ is to be defined, and the appropriate test for ‘prejudice to reputation or honour’ remains a question of some uncertainty. In particular, it is not entirely clear whether mere offence on the author’s part is sufficient or whether objective harm to the author’s reputation is required. This article seeks to endorse the objective test adopted in the United Kingdom (‘UK’) and other common law jurisdictions for ‘prejudice to reputation or honour’ in relation to the moral right of integrity, but argues that a strict objective standard that is rigidly applied to all works can lead to unfairness in some cases, and should be tempered by a doctrine of ‘presumed prejudice’ for works of tangible visual art that have been modified without authorisation. Of the ‘common law’ jurisdictions compared in this article — the UK, Canada and Australia — only Canada currently prescribes a framework of ‘presumed prejudice’ for modified works of tangible art in its domestic copyright legislation. This article explores the feasibility of transplanting the Canadian framework for presumptive prejudice into the Australian copyright system, so as to bring about a fairer distribution of power between authors and users of visual artwork.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.248
Teacher spread0.221 · 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.

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
Published2016
Admission routes1
Has abstractyes

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