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Record W2341662179 · doi:10.14288/1.0077600

Balancing the legal teetertotter : finding the appropriate weight for creator and user rights in cyber space

2010· article· en· W2341662179 on OpenAlexaboutno aff
Kenneth Richard Cavalier

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)Computer scienceCyber SpaceComputer securityInternet privacyPolitical scienceBusinessWorld Wide WebThe Internet

Abstract

fetched live from OpenAlex

This study represents a "quantum analysis" Law Reform approach to the adoption and evaluation of Canadian and international legal regimes aimed at the protection of intellectual property rights (IPRs) such as copyright, patent and trade-marks in cyberspace. Related intangible property rights such as privacy, publicity, performance, exhibition, moral rights, P2P file-sharing, "grey marketing" and protection against misappropriation are therefore considered. Beginning with a review of appellate level case law to identify areas of uncertainty and new developments in contemporary IP law, especially on the Internet, the history and the philosophical justifications for granting of traditional IPR protection of limited duration to creators are noted. The nature of the IPRs granted and the remedies available to enforce them are presented A review of current IP practice and remedies notes the trend of the Supreme Court of Canada to strive for balance among the stakeholders, both creators and users, of the intangible property. The post-1994 TRIPS agreement and globalization are discussed and the intersection between IP law, national sovereignty, and international trade through the WTO is considered. Canada’s capability to fashion its own legal response in the face of her international responsibilities and TRIPS pressure to harmonize IP law is assessed. A discussion of the merits of sui generis IP laws for use in the new digital knowledge-based economy environment rather than the extension of traditional IP laws to remove current uncertainties follows. The study concludes with a list of fifty recommendations for characteristics of any legislative solution proposed for IPR protection on the Internet. The requirement of a balanced regime is affirmed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.205
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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