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Record W7004334455

Latin America

2012· other· en· W7004334455 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2012
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansFree trade agreementFree tradeNegotiationTrade agreementMexican StateOrder (exchange)State (computer science)Politics
DOInot available

Abstract

fetched live from OpenAlex

As political and economic reforms swept through Central America, leaders who once sought to distance themselves from the United States now began to forge closer ties with the U.S. Like many other Middle and South American countries, Mexico was in the process of privatizing its economy and actively sought foreign investment in order to stimulate development. Encouraged by the 1989 free trade agreement signed between Canada and the U.S., Mexico and the U.S. began negotiations over what would become the North American Free Trade Agreement, however domestic concerns about the agreement from both sides hindered the negotiation process. In the U.S., critics claimed any free trade agreement would cost American jobs, while proponents trumpeted the agreement as a way to bolster the economy and make the United States more internationally competitive with Japan. On the other side of the border, Mexican lawmakers sought to balance the need to expand Mexico's markets with the fear of reducing their country to a source of cheap labor for the U.S. Will a free trade agreement encourage more liberal global trade, boosting both the Mexican and American economies, or will it cost American jobs and limit Mexican advancement? In this episode, Peter Hakim of the Inter-American Dialogue and Mexican Journalist Jose Manuel Nava discuss the state of Latin American economies, as well as the proposed trade agreement's potential ramifications.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.004
GPT teacher head0.164
Teacher spread0.159 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes1
Has abstractyes

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