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Record W2029457790 · doi:10.1177/0270467607300641

Intellectual Property Law as an Internal Limit on Intellectual Property Rights and Autonomous Source of Liability for Intellectual Property Owners

2007· article· en· W2029457790 on OpenAlexaff
Elizabeth F. Judge

Bibliographic record

VenueBulletin of Science Technology & Society · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIntellectual propertyTangible propertyLaw and economicsIntangible propertyProperty lawLawLiabilityNumerus claususPublic propertyBusinessProperty rightsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This article considers the interplay between intellectual property rights and classic property rights raised by Hoffman v. Monsanto (2005) and advances the idea that intellectual property law can serve as an autonomous source of liability for intellectual property owners. The article develops the conceptual advantages of demarcating physical and intellectual properties and allocating rights and responsibilities based on the respective property sphere. It introduces a theoretical Hohfeldian framework, in which the grant of a positive limited-term monopoly right entails a corresponding duty, to establish intellectual property law as a source of internal limits on intellectual property rights. The article is a prolegomena to a detailed matrix of those rights and duties within intellectual property law. This matrix could support patentee duties that go beyond public disclosure of the invention and could establish patent law as an alternative legal framework to tort law to address harms caused by inventions.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.011
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.044
GPT teacher head0.241
Teacher spread0.197 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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