Competitividad comercial de la carne de ganado bovino entre los países miembros del TLCAN 1997-2008.
Bibliographic record
Abstract
El presente trabajo analiza la competitividad comercial de carne de ganado bovino entre los países miembros del Tratado de Libre comercio de América del Norte (TLCAN): México, Canadá y Estados Unidos. La metodología utilizada es mediante indicadores de mercado: participación de mercado, coeficiente de ventaja comparativa revelada (CVCR), tasa de penetración de las importaciones (TPI) y producción expuesta a la competencia (PEC), para ello se utilizan datos del periodo 1997-2008, comparando los valores promedio de 1997 a 1999 contra los valores promedio de 2006 a 2008. Esto permite observar el desarrollo de la competitividad de los 3 socios comerciales a nivel mundial y permite evaluar la competitividad de Canadá y México como principales proveedores de carne de ganado vacuno del mercado estadounidense. Los resultados de competitividad para Canadá en el mercado de importaciones estadounidenses de carne de ganado bovino se ha visto mermada; mientras que la competitividad de México en este sector se ha incrementado como resultado de la apertura comercial. _______________ TRADE COMPETITIVENESS OF THE MEAT OF CATTLE BETWEEN THE COUNTRIES MEMBERS OF NAFTA 1997-2008. ABSTRACT: The present work analyzes the trade competitiveness of beef cattle among the member countries of the North American Trade Agreement (NAFTA), Mexico, Canada and the United States. The methodology used by market indicators, market share, revealed comparative advantage coefficient (CVCR), rate of import penetration (TPI) and production exposed to competition (PEC); in the study, data from the period 1997 - 2008, comparing the average values from 1997 to 1999 against the average values from 2006 to 2008. This allows us to observe the development of the competitiveness of the 3 partners worldwide and evaluates the competitiveness of Canada and Mexico as major suppliers of beef cattle in the U.S. market. The results for Canada competitive in the market for U.S. imports of beef cattle have been weakened, while Mexico's competitiveness in this sector has increased as a result of trade liberalization.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".