Maturity Level of Rural Leaders in Selected Paddy Farming Technologies in Muda Agricultural Development Authority (MADA) -Malaysia
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Bibliographic record
Abstract
<p>To provide good leadership it is necessary for individuals and groups to help bring a rural community to action. As the rural leaders play a function in important programs in agricultural extension. However, The study was conducted to determine the maturity of rural leaders based on maturity model theory towards agricultural technologies In Malaysia Paddy Farming, and explore the relationship between the selected characteristics of the respondents. Data were collected through personal interview from 260 randomly selected in muda agriculture development authority MADA area. A five point Likert scale was used to determine the maturity of rural leaders ranged from 1 = never to 5= always.The majority (63.1%) of the respondents had a moderate level of maturity. The correlation analysis between socio-demographic characteristics and maturity level show that there is a positive and significant relationship between variables age and years of experience in paddy farming, at 0.05 level of significance.</p>
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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