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Record W2231172519

Twenty Years of Legal History (Making) at the Copyright Board of Canada

2011· article· en· W2231172519 on OpenAlexaffabout
Jeremy de Beer

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStatutory lawMainstreamLegislative historyPolitical sciencePresentation (obstetrics)Best practiceStatutory interpretationLaw and economicsCopyright ActStakeholderLawPublic administrationIntellectual propertyCopyright lawSociology
DOInot available

Abstract

fetched live from OpenAlex

During the past 20 years, more or less, copyright has evolved from a relatively obscure area of specialized legal practice to a topic at the forefront of public consciousness and policy debates. This metamorphosis might be due to technolog- ical innovation, social practices, commercial developments, or, most likely, some combination of those and other things. Mainstream media coverage is probably the best barometer of copyright’s growing importance, but there has also been a discernable increase in the judiciary’s attention to the issues.Professor de Beer’s presentation seeks to underscore the crucial contributions of the Copyright Board on some of the most inter- esting and important copyright law matters decided during the past two decades. From concep- tual challenges to the integrity of the collective management system to policy choices about the balancing of stakeholder interests to technical disputes about over statutory interpretation, the Board has been instrumental in defining the shape of copyright practice in Canada today. As new copyright challenges continue to arise over the coming decades, the Board’s role is predicted to grow even larger.

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)0.016
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0330.019
Scholarly communication0.0220.005
Open science0.0020.004
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0240.003

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 head0.017
GPT teacher head0.181
Teacher spread0.165 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

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