MétaCan
Menu
Back to cohort
Record W2989705747 · doi:10.35429/jbds.2019.15.5.14.20

Dynamism and competitiveness of mexican beef, a focus of market diversification

2019· article· en· W2989705747 on OpenAlexaboutno aff
Rebeca Yurani Carrillo-Ángeles, Emmanuel Cruz-Soriano, Zugaide Escamilla Salazar

Bibliographic record

VenueJournal of Bussines Development Strategies · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsDynamismDiversification (marketing strategy)International tradeInternational economicsCompetition (biology)Free tradeIndex (typography)EconomicsBusinessProduct (mathematics)Revealed comparative advantageProduction (economics)Investment (military)Comparative advantageMacroeconomics

Abstract

fetched live from OpenAlex

In Mexico, the production and export of bovine have remained competitive, placing it within the top ten countries due to its competitiveness which is based on weather conditions, the production of cereals for food and the commercial relationship with the United States. In this regard, Mexico, with the signing of the North American Free Trade Agreement (NAFTA), promotes international trade with the United States and Canada, with the objective of eliminating obstacles to trade, facilitating the cross-border circulation of goods and services, promoting fair competition in the free trade zone, increases investment opportunities, among others aims (Ministry of Economy, 1993). At the beginning of the agreement, Mexico achieved short-term macroeconomic objectives of stability, economic growth, and inflation control, however, in the long term it has not meant an increase in the standard of living of Mexicans, therefore, Mexico decided to diversify markets of export through bilateral trade agreements with other countries. As a consequence, the objective of this research is to perform an analysis of the commercial position of Mexican beef (2002-2016), obtaining the Grubel & Lloyd index and the grown rate by time interval, concluding that there is a commercial dynamism of this Mexican product.

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: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.461

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 communication0.0000.001
Open science0.0000.000
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 head0.012
GPT teacher head0.206
Teacher spread0.195 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Bussines Development StrategiesSame topicGlobal Trade and CompetitivenessFrench-language works237,207