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Record W2922505003

Hacia el mercado común norteamericano (Towards a North American Common Market)

2010· article· es· W2922505003 on OpenAlexaboutno aff
José Flores Salgado, Federico Novelo Urdanivia

Bibliographic record

VenueRevista Análisis Económico · 2010
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceEconomyGeographyForeign direct investmentWelfare economicsEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

El articulo analiza los resultados menguados y menguantes que el Tratado de Libre Comercio de America Latina arroja para la economia mexicana. Destaca como otros proveedores del mercado regional (China y algunos paises del caribe) participan con ventajas similares y desplazan la produccion de Mexico, al tiempo que tienden a absorber una proporcion cre- ciente de la inversion extranjera directa que llega a los paises no desarrollados. Se formula una propuesta de integracion de mayor intensidad: El Mercado Comun Norteamericano, con ventajas visibles para Canada, EUA y Mexico. Clasificacion JEL: F10, F13, F15 Abstract The article analyzes the increasingly poor results that the North American Free Trade Agreement has had for the Mexican economy. It also emphasizes how other suppliers to this regional market (such as China, and some Caribbean countries) enjoy similar advantages to Mexico, and are displacing Mexican products, at the same time as they absorb a growing proportion of direct foreign investment to lesser developed countries. A proposal for a more profound integration process is formulated: The North American Common Market; with visible advantages for Canada, the United States and Mexico.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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