The Role of Human Capital in Strengthening Horticultural Agribusiness Institutions: Evidence from Structural Equation Modeling
Why this work is in the frame
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Bibliographic record
Abstract
Farmers' engagement in agribusiness institutional activities has largely been confined to production activities, and has not been fully optimized. Similarly, the role of agricultural extension workers in providing institutional assistance has been narrowly scoped, mostly limited to government-initiated programs focusing on infrastructure development and production enhancement. Human capital, a vital factor for agribusiness development, has been largely overlooked. This study, therefore, seeks to investigate the influence of human capital components on the strengthening of horticultural agribusiness institutions, with farmer participation and coordination between farmer institutions as mediating factors. The research was conducted in the Uluere Sub-district, Bantaeng District, South Sulawesi Province, Indonesia, a region known for horticultural agribusiness development. Data from 120 randomly selected respondents were analyzed using Structural Equation Modelling (SEM) to accomplish the research objective. The findings revealed that leadership, a component of human capital, has a direct, positive, and statistically significant influence on institutional strengthening. However, participation does not serve as a mediator between human capital components and the strengthening of horticultural agribusiness institutions. The variable of coordination function partially mediates between leadership and institutional strengthening, while the effectiveness of teamwork fully mediates the impact on institutional strengthening.
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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 | 0.000 | 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 | 0.001 |
| 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 it