The Japan-Mexico Fta: A Cross-Regional Step in the Path towards Asian Regionalism
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".