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Record W3014508495

The Trans-Pacific Partnership, Copyright Law and Education

2015· article· en· W3014508495 on OpenAlexaboutno aff
Matthew Rimmer

Bibliographic record

VenueThe Advocate · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual propertyGeneral partnershipParliamentEnforcementDozenTrade agreementPolitical scienceAtlantaPublic administrationLawGeographyNegotiationPolitics
DOInot available

Abstract

fetched live from OpenAlex

There is much concern across the Pacific rim about the impact of the Trans-Pacific Partnership (TPP) upon public education. The secretive trade agreement involves a dozen nations across the Pacific, including Australia, New Zealand, Canada and the United States, and Indonesia may soon join. Although the text was finalised at the Atlanta talks in October 2015, the Agreement has not yet been made public. (The NTEU has joined with other unions and civil society organisations in calling for the agreement to be revealed to facilitate public debate before any decisions are made by Parliament.) So whilst we cannot examine all the text that may impact on public educations, WikiLeaks has published the final version of the Intellectual Property Chapter of the TPP. The Intellectual Property Chapter of the TPP alone, with its copyright term extension, limits on copyright exceptions, and enforcement measures, will have a significant impact for educators and public education.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.019
Scholarly communication0.0170.012
Open science0.0010.006
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0160.002

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 head0.035
GPT teacher head0.306
Teacher spread0.271 · 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
Published2015
Admission routes1
Has abstractyes

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