Estimation of competitiveness indicators in avocado importing markets
Bibliographic record
Abstract
Objective: The main objective of the work was to analyze the competitiveness of avocados produced in Mexico during the study period from 1995 to 2019 in the world market, derived from the production surplus.Design/Methodology/Approach: The methodological design contemplated the use of trade competitiveness indicators at the level of importing world markets, the Revealed Comparative Advantage Index and the Normalized Revealed Comparative Advantage Index were calculated, data on avocado exports were analyzed as well as total agricultural exports made by Mexico to the world, and specifically to countries such as the United States, Canada and Japan.Results: The results obtained suggest that avocado production in Mexico is highly competitive at the international level.Study Limitations/Implications: The importance of making an analysis of the main avocado production variables was to locate the situation of products coming from Mexico with respect to the world situation.Findings/Conclusions: Internationally, Mexican avocado production stood out in first place, with 2.4 million tons and 1.3 million tons of avocado were destined for export in 2019, contributing more than 45% of the world export market. These exports represented a very significant percentage of avocado imports in countries such as the United States of America, Canada, Japan, Europe and Central America. Currently, 100% of the national requirements are satisfied with domestic production; likewise, world imports have increased 171.97% in the last decade.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".