Agronegocios: ¿Qué piensan los jóvenes egresados de escuelas y facultades de negocios en México sobre el emprendimiento en el sector agropecuario?
Bibliographic record
Abstract
Objective: To know what young graduates of schools and business faculties in Mexico think about undertaking (or investing) in the agricultural sector and identify what are the determining factors that affect how to start an agribusiness. Design/methodology/approach: A sample of 3,213 young graduates from a database generated by the Business Development Center of the Universidad Autonoma de Nuevo Leon during the first quarter of 2019 was used. With the information collected a model was made of structural equations that explain the way in which young people classify their perceptions on the subject of study. Results: Young graduates of schools and business faculties in the south of the country give greater weight (44.3%) to the commitment they consider to have with Mexican agriculture and to the satisfaction of knowing that if they undertake an agribusiness, they will help their communities, while young graduates from the north of the country value more the economic remuneration they could generate if they start a business of this type (35.4%). Study limitations/implications: The work performed is not comparable and generalizable, so that expanding the population or sample at regional or national level, the research would have a scope of representative analysis on the phenomenon of study.Findings/conclusions: Most of the young people surveyed seem to have a positive perception about the importance of the agricultural sector. However, more than half of the sample interviewed (57.9%) argues that it would not put an agribusiness in this sector.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".