Competitiveness in Michoacán: A Proposal for an International Positions in Agroindustrial Sector
Bibliographic record
Abstract
The present research has as aim, to determine the ways in which are affected the quality, the price, the technological innovation, the environmental management, the market and the public agro industrial policies in the international competitiveness of the agro industrial sector of Michoacan. It was located 51 agroindustrial companies that are exporting. It was used as instrument of compilation of information a questionnaire composed of 80 items. Once the information was processed, it was determined the correlational analysis, linear regression and attempts at hypothesis. We can see with the results that the state is competitive in this sector and that the variables explain 97% of the competitiveness. The variable that determined the competitiveness with greater proportion was the technological innovation, so it requires public policies that strengthen this indicator and the sector can be even more competitive. In the other hand public polices in agro business got the lowest score and there is a gap in the implementation of programs and modernization in the sector that causes both nationally and internationally doesn´t be strong in the area of agribusiness Michoacan, so it must strengthen these policies from the national development plan.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".