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Record W2981446419

Vínculos productivos en América del Norte

2019· article· es· W2981446419 on OpenAlexaboutno aff
Miguel Pérez Ludeña

Bibliographic record

VenueSede Subregional de la CEPAL en México (Estudios e Investigaciones) · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicRegional Development and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEuropean unionPolitical scienceHumanitiesBusinessArtInternational trade
DOInot available

Abstract

fetched live from OpenAlex

Las economias del Canada, los Estados Unidos y Mexico estan fuertemente unidas entre si, aunque esta union no es equilibrada y tampoco se ha incrementado durante los 25 anos del Tratado de Libre Comercio de America del Norte (TLCAN). El espacio economico que se ha creado en America del Norte ha facilitado el desarrollo de cadenas de valor en estas industrias y esto ha permitido a las empresas enfrentar con exito la fuerte competencia internacional, especialmente la de Asia. Para Mexico, la integracion ha desarrollado mucho la industria exportadora pero no se ha traducido en convergencia en el ingreso con los Estados Unidos y el Canada. Mexico ha aprovechado sus ventajas comparativas, pero no ha conseguido atraer inversiones que aumenten el valor anadido en el pais, ni tampoco aquellas intensivas en actividades de I+D. Ademas, el tipo de industrias que la integracion con America del Norte ha promovido no ha ayudado a la integracion territorial del pais, que continua siendo extremadamente desigual.

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)0.003
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.012
GPT teacher head0.275
Teacher spread0.263 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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