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Record W1132858255 · doi:10.1017/cbo9781107707207.005

An Overview of the Agreement

2014· book-chapter· en· W1132858255 on OpenAlexaboutno aff
Frederick M. Abbott

Bibliographic record

VenueCambridge University Press eBooks · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAgreementPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Introduction The Anti-Counterfeiting Trade Agreement (ACTA) is a signed international agreement that is pending ratification and entry into force. Signature and initial membership are limited to the group of countries which participated in its negotiation, and others that may be agreed to by consensus. The negotiating participants are the member states of the European Union (EU) as well as Australia, Canada, Japan, South Korea, Mexico, Morocco, New Zealand, Singapore, Switzerland and the United States. Negotiation of ACTA provoked controversy from the outset. Proponents characterised it as an exercise needed to address an ongoing threat to the interests of intellectual property right (IPR) owners, as well as to defend the public against risks posed by goods coming from unreliable sources. Opponents portrayed ACTA negotiations as driven by IPR holder groups intent on moving their high-protection agenda away from multilateral institutions towards a more hospitable forum. In the multilateral organisations, a range of interested groups participate in negotiations, and the results should appropriately balance legitimate interests (if common ground can be found). The ACTA negotiating forum, by way of contrast, was predisposed to favour particular IPR holder objectives. The initially proposed ACTA texts threatened to create an international trade and technology transfer environment, including in digital space, with serious obstacles to access for important public goods, including medicines and information. Proposed criminalisation measures were unbalanced. Ultimately, a number of the most troublesome elements of the initial proposals were dropped, alleviating some of the most pressing worries.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.071
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.003
Scholarly communication0.0090.009
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0710.034

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 head0.071
GPT teacher head0.272
Teacher spread0.201 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicEuropean and International Law StudiesFrench-language works237,207