MétaCan
Menu
Back to cohort
Record W2317038274 · doi:10.5509/201689175

Playing Both Sides of the Pacific: Latin America's Free Trade Agreements with China

2016· article· en· W2317038274 on OpenAlexvenueno aff
Carol Wise

Bibliographic record

VenuePacific Affairs · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsChinaInternational tradeLatin AmericansFree tradeFree trade agreementAsia pacificPolitical scienceInternational economicsBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

One of the most prominent trends in Latin America in the 2000s has been the proliferation of bilateral free trade agreements (FTAs) across the Pacific basin. Beginning with the path-breaking Chile-Korea FTA in 2004 up to the Costa Rica-Singapore FTA in 2013, the past decade has seen the negotiation of twenty-two cross-Pacific accords. China, too, has jumped on to the cross-Pacific FTA bandwagon, including its negotiation of separate bilateral FTAs with Chile (2006), Peru (2009), and Costa Rica (2011). This paper analyzes the origins, content, and preliminary outcomes of these three China-Latin America FTAs. The findings are threefold: 1) in contrast with other cross-Pacific FTAs, which include at least one developed country, the three FTAs analyzed in this paper constitute “south-south” FTAs; yet, in contrast with other south-south FTAs, these three China-Latin America accords approximate WTO+ standards vis-à-vis the World Trade Organization (WTO) and its new trade agenda (services, investment, and intellectual property rights); 2) although the motives for negotiating these developing- developing country accords varied, on the part of China and the countries themselves, this did not disrupt the march toward WTO+ status; and 3) while all three of these FTAs elude standard theoretical explanations for the negotiation of bilateral FTAs, the three Latin American countries do share similar reform trajectories and institutional affinities, which sheds light on the decision and capacity of each to negotiate a bilateral FTA 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.562

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.183
Teacher spread0.158 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations65
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePacific AffairsSame topicGlobal trade and economicsFrench-language works237,207