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Record W3124936903

TPP and Trans-Pacific Perplexities

2014· article· en· W3124936903 on OpenAlexaboutno aff
Peter K. Yu

Bibliographic record

VenueFordham international law journal · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)Political scienceContext (archaeology)DemocracyNegotiationAccountabilityIntellectual propertyGeneral partnershipInternational tradePublic administrationDevelopment economicsBusinessEconomicsLawGeographyPolitics
DOInot available

Abstract

fetched live from OpenAlex

In the past few years, the United States has been busy negotiating the Trans-Pacific Partnership (TPP) Agreement with countries in the Asia-Pacific region. These countries include Australia, Brunei Darussalam, Canada, Chile, Japan, Malaysia, Mexico, New Zealand, Peru, Singapore and Vietnam. Although it remains unclear which chapters or provisions will be included in the final text of the TPP Agreement, the negotiations have been quite controversial. In addition to the usual concerns about having high standards that are heavily lobbied by industries and arguably inappropriate for many participating countries, the TPP negotiations have been heavily criticized for their secrecy and lack of transparency, accountability and democratic participation. Written for the inaugural annual Asia-Pacific issue of the Fordham International Law Journal, this article does not seek to continue this line of criticism, although transparency, accountability and democratic participation remain highly important. Nor does the article aim to explore the agreement's implications for each specific trade sector. Instead, this Article focuses on the ramifications of the exclusion of four different parties or groups of parties from the TPP negotiations: (1) China; (2) BRICS and other emerging economies; (3) Europe; and (4) civil society organizations. Targeting these "TPP outsiders" and using illustrations from the intellectual property sector and the larger trade context, this article seeks to highlight the perplexities created by the TPP negotiations. It cautions policymakers, commentators and the public at large against the negotiations' considerable and largely overlooked costs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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.

Study designTheoretical or conceptual
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

Citations4
Published2014
Admission routes1
Has abstractyes

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