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Record W1544806039

Secondary Markets for Copyrighted Works and the ‘Ownership Divide’: Reconciling Competing Intellectual and Personal Property Rights

2010· article· en· W1544806039 on OpenAlexaff
Wendy A. Adams

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsMcGill University
Fundersnot available
KeywordsCopyingIntellectual propertyPublic interestLaw and economicsBalance (ability)Exclusive rightLegislatureProperty rightsBusinessPublic domainMoral rightsNormativeIncentiveLawEconomicsPolitical scienceMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The weight of precedent supports restricting the ability of copyright holders to control post-purchase modification and resale in secondary markets. To find infringement in the absence of copying disrupts clear and intentional legislative distinction between economic and moral rights. The economic rights conferred by intellectual property law do not affect the purchaser’s personal property rights to deal with the transferred tangible good, provided that any subsequent modification deals only with the tangible good and does not multiply the occurrences of the protected work. Precedent alone, however, is not a complete answer to novel legal questions. Consideration of underlying first principles upon which doctrinal rules are based is also required. From this perspective, the freedom to operate in secondary markets is consistent with the normative basis of copyright law: (a) copyright is a balance between the necessary incentives to create and the public interest in the encouragement and dissemination of works; and (b) in achieving the appropriate balance between these two goals, over-compensation is as much a cause for concern as undercompensation, lest the rights of copyright holders expand to the detriment of the public interest.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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 designOther design
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
Published2010
Admission routes1
Has abstractyes

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