Linear Structural Relationship Model of Servant Leadership of School Administrators Affecting Effectiveness of Primary Schools in The Northeast
Why this work is in the frame
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Bibliographic record
Abstract
This research aims to develop a structural relationship model of servant leadership among educational administrators that impacts the effectiveness of primary schools in northeastern Thailand and to examine the model’s alignment with empirical data. The study is conducted in two phases: Phase 1 involves developing a structural linear model of servant leadership among educational administrators that affects the effectiveness of primary schools in northeastern Thailand, and Phase 2 tests the model’s consistency with empirical data. The sample consists of 500 administrators and teachers from the 2021 academic year. The data collection instrument is a rating scale questionnaire measuring school effectiveness, with discriminative power values between 0.44 – 0.81 and reliability of 0.98, and a servant leadership factor with discriminative power values between 0.22 – 0.87 and reliability of 0.98. Data analysis includes frequency, percentage, mean, standard deviation, Pearson correlation coefficient, and structural linear modeling using specialized software. The research findings indicate that: 1) The structural linear model of servant leadership among educational administrators impacting primary school effectiveness in northeastern Thailand includes five dimensions: Vision, with three observable variables; Awareness, with three observable variables; Understanding and Valuing Others, with three observable variables; Staff Development, with three observable variables; and Service, with five observable variables. School effectiveness comprises four observable variables. 2) The developed model is consistent with the empirical data, with a Chi-square (χ²) value of 159.66, degrees of freedom (df) of 137, a p-value of 0.09, a relative Chi-square (χ²/df) of 1.17, RMSEA of 0.02, GFI of 0.97, and AGFI of 0.95.
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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 | 0.002 |
| 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 | 0.000 |
| 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