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Record W3121308946 · doi:10.31235/osf.io/uh4bn

Beyond Refusal to Deal: A Cross-Atlantic View of Copyright, Competition and Innovation Policies

2016· article· en· W3121308946 on OpenAlexaff
Ariel Katz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntellectual propertyLicenseCompetition (biology)Context (archaeology)Law and economicsCompetition lawEuropean unionDoctrineLawExpansiveBusinessRule of reasonPolitical scienceEconomicsInternational tradeMonopolyMarket economy

Abstract

fetched live from OpenAlex

Conventional wisdom holds that the European Union has opted to apply its competition law to the exercise of intellectual property rights to a much greater extent than has the United States. We argue that, at least in the context of copyright protection, this conventional wisdom is false. While European antitrust regulation of refusal to license one's intellectual property does seem much more robust and activist than U.S. antitrust regulation of similar conduct, focusing solely on one narrow aspect of antitrust doctrine — the treatment of a unilateral refusal to deal — tells less than half the story.Once various doctrines of copyright law are taken into account, the substantive difference between the European and American approaches not only narrows, but in some key respects is reversed. While European jurisdictions have relatively expansive copyright protection which may require antitrust intervention to check anti-competitive uses of copyrighted works, American copyright law provides stronger internal limits on copyright protection, which thereby lessens the need for resort to antitrust law as an external check on anti-competitive uses of copyrighted works. Furthermore, when the broader impact that antitrust law might have on the exercise of IPRs in the United States is considered (not only in substance, but also in antitrust process), it becomes apparent that in key respects, when innovative-competition is at stake, U.S. law grants overall weaker copyright protection than that available in Europe. We also explain why the two jurisdictions have adopted distinct approaches to resolving similar problems and evaluate those approaches.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0050.028
Scholarly communication0.0220.024
Open science0.0020.005
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0090.001

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 head0.041
GPT teacher head0.347
Teacher spread0.306 · 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 designTheoretical or conceptual
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

Citations2
Published2016
Admission routes1
Has abstractyes

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Same topicIntellectual Property LawFrench-language works237,207