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Record W2329672484 · doi:10.5509/2007802279

The Japan-Mexico Fta: A Cross-Regional Step in the Path towards Asian Regionalism

2007· article· en· W2329672484 on OpenAlexvenueno aff
Mireya Solís, Saori N. Katada

Bibliographic record

VenuePacific Affairs · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsnot available
Fundersnot available
KeywordsRegionalism (politics)Path (computing)Political scienceGeographyComputer sciencePolitics

Abstract

fetched live from OpenAlex

Introduction To most observers, Japan and Mexico seem distant economic partners, with only a modest volume of bilateral' trade and foreign direct investment and a large geographical and cultural gulf between them. By this account, the Japanese decision to negotiate with Mexico is puzzling if not downright nonsensical. Why would Japan invest so much political capital in the negotiation of a complex free trade agreement (FTA) with a nation accounting for such a minuscule share of its international economic exchange?1 We challenge this interpretation of Japan's second FTA ever and demonstrate that far from irrational or insignificant, the stakes involved in the Japan-Mexico FTA were very high. This cross-regional initiative stands to exert powerful influence over the future evolution of Japan's turn towards economic regionalism.2 For a number of Japanese industries (automobiles, electronics, and government procurement contractors) , negotiating with Mexico was essential to level the playing field vis-a-vis their American and European rivals already with preferential access to the Mexican market based on their FTAs. For the Japanese trade bureaucrats, housed in the Ministry of Economy, Trade and Industry (METI), the stakes of the trade agreement with Mexico were also very high; not only would it enable Japan to use bilateral trade deals as an instrument to counter trade diversion abroad, but it would also be crucial in setting precedents on negotiation modalities regarding issues such as service liberalization or rules of origin (ROO). In addition, it would be all-important in helping the ministry tip the domestic balance in

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.004
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.237
Teacher spread0.209 · 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

Citations55
Published2007
Admission routes1
Has abstractyes

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