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Valor agregado y cadenas globales de las exportaciones entre México, Estados Unidos y Canadá

2022· article· es· W4286592287 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProblemas del Desarrollo Revista Latinoamericana de Economía · 2022
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

El objetivo del presente trabajo es descomponer por origen y destino el valor agregado contenido en las exportaciones bilaterales de los países integrantes del Tratado entre México, Estados Unidos y Canada (T-MEC) en los años 2005, 2010 y 2015, para identificar así, la proporción del valor agregado interno (VAI) que cada país exporta y el tipo de participación de cada uno en las cadenas de valor de la región. Se utilizó un modelo de insumo-producto en valor-agregado con las matrices interregionales de la Organización para la Cooperación y el Desarrollo Económicos (OCDE) para los años antes mencionados. De esta forma, los resultados obtenidos sugieren que las exportaciones mexicanas son las de mayor valor agregado extranjero (VAE); México y Canadá se han insertado de manera superficial a las cadenas de valor de la región, mientras que EU mantiene cadenas complejas con sus socios comerciales.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, 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 score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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