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Record W2123094782 · doi:10.19173/irrodl.v5i3.205

Stealing the Goose: Copyright and Learning

2004· article· en· W2123094782 on OpenAlexaffvenue
Rory McGreal

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsAthabasca University
Fundersnot available
KeywordsIntellectual propertyFair useCommonwealthDigital Millennium Copyright ActThe InternetLaw and economicsCopyright infringementCommonsCopyright ActBalance (ability)Internet privacyFair dealingBusinessLawPolitical sciencePublic relationsCopyright lawEconomicsComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The Internet is the world's largest knowledge common and the information source of first resort. Much of this information is open and freely available. However, there are organizations and companies today that are trying to close off the Internet commons and make it proprietary. These are the “copyright controllers.” The preservation of the commons and expanding access to digital content and applications are very important for distance educators. The educational exemptions for “fair use” in the United States and “fair dealing” in the Commonwealth countries are integral to any understanding of copyright, which was instituted for the dissemination of knowledge, and not, as is commonly believed, to protect the rights of the copyright owners. Copyright law was expressly introduced to limit their rights. Yet, these controllers are successfully turning a “copy” right into a property right. The traditional rights of learning institutions are being taken away. The balance for researchers should be restored. Research and learning must be allowed the broad interpretation that was intended in the original laws. Keywords: copyright; intellectual property; infringement; Internet; stealing; balance

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.022
Scholarly communication0.0120.017
Open science0.0010.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0140.002

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 head0.087
GPT teacher head0.379
Teacher spread0.292 · 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.

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

Citations12
Published2004
Admission routes2
Has abstractyes

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