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Record W2059514626 · doi:10.7202/1013011ar

Trademarks Worth a Thousand Words : Freedom of Expression and the Use of the Trademarks of Others

2012· article· en· W2059514626 on OpenAlexaffvenueabout
Teresa Scassa

Bibliographic record

VenueLes Cahiers de droit · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTrademarkIntellectual propertyFreedom of expressionExpression (computer science)The InternetLawBusinessPhenomenonPolitical scienceLaw and economicsAdvertisingSociologyHuman rightsComputer sciencePhilosophyEpistemologyWorld Wide Web

Abstract

fetched live from OpenAlex

Trademarks play an important role in facilitating critical speech in an increasingly corporate capitalist society. Not only do they serve as markers for expressive content on the Internet, they can also be used as vehicles for the communication of critical messages about the trademark owner or its products or services. In this paper, the author examines the implicit balance in the Trade-marks Act between freedom of expression values and trademark rights, and argues that it is being significantly altered by the contemporary push for greater trademark protection. The author identifies specific problems that emerge from Canadian case law relating to freedom of expression and trademark law. These include the treatment by courts of intellectual property rights as private property rights, inattention to the trademark/copyright overlap, the troublesome distinction between commercial and non-commercial uses, and the phenomenon of trademark bullying. The author argues for a sharp evolution in Canadian case law that would establish clear parameters for critical speech using trademarks.

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)0.005
metaresearch head score (Gemma)0.013
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 score0.344
Threshold uncertainty score0.685

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.046
Scholarly communication0.0110.008
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.243
Teacher spread0.217 · 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

Citations5
Published2012
Admission routes3
Has abstractyes

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