Export Diversification: Strategy for International Trade of the Automotive Sector in Mexico Category
Bibliographic record
Abstract
The automotive industry has important and strategic relevance in Mexico’s economic growth. Since its inception in this country, it has provided a source of global expansion in terms of international marketing; however, over the years, there has been a significant trend of little diversification in the export of the specific products of this sector of the Mexican economy, concentrating the largest percentage of its trade towards the United States and setting aside the incursion into economies such as Canada, with which the T-MEC (Government of Mexico) treaty is, (2019) which represents some benefits for the distribution of goods and services between the countries of Mexico, USA and Canada, which in this regard are not being properly exploited by Mexico by concentrating its exchange of automotive goods in the United States. According to Wells and Wint (2000), one of the alternatives to mitigate this commercial centralization in the automotive industry is outside Mexican borders, through attracting foreign investment and achieving greater export diversification. The methodology used for this research is qualitative in focus. It focuses on the technique of documentary review through a descriptive explanatory study, which results in a historical comparison of the export percentages of the automotive sector by Mexico from 2018 to 2021. Finally, it concludes by describing the impacts that arise concerning the international promotion of the country in terms of foreign trade by not taking advantage of the international agreements and treaties in force.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".