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Record W3121171316

Understanding the Trans-Pacific Partnership

2013· preprint· en· W3121171316 on OpenAlexaboutno aff
Jeffrey J. Schott, Barbara Kotschwar, Julia Muir

Bibliographic record

VenueRePEc: Research Papers in Economics · 2013
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipDynamismNegotiationPolitical scienceChinaInternational tradeEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

The Trans-Pacific Partnership (TPP) is a big deal in the making. With the Doha Round of multilateral trade negotiations at an impasse, the TPP negotiations have taken center stage as the most significant trade initiative of the 21st century. As of December 2012, negotiators have made extensive progress in 15 negotiating rounds since the talks began in March 2010, though hard work remains to finish the deal in the coming year or so. Despite this effort, however, the TPP is not well understood. In part, the reason lies in the dynamism of the TPP initiative. Unlike other free trade pacts, the growing membership as the talks have proceeded and the broad range, complexity, and novelty of the issues on the agenda have made it difficult to track the substantive detail and progress of the talks. This Policy Analysis aims to remedy this problem by providing a reader's guide to the TPP initiative. It first assesses how much the TPP countries are alike and like-minded in their pursuit of a comprehensive trade deal. It then examines the current status of the talks, the major substantive sticking points, and the implications of Canada and Mexico joining the talks as well as prospective membership of other countries. The Policy Analysis then looks ahead to how the TPP could advance economic integration in the Asia-Pacific region and the implications for trade relations with China.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.291
GPT teacher head0.308
Teacher spread0.017 · 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

Citations54
Published2013
Admission routes1
Has abstractyes

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