Investigation of Teacher Job-Performance Model: Organizational Culture, Work Motivation and Job-Satisfaction
Bibliographic record
Abstract
The research is intended to develop a Teacher Job-performance Model by considering causal relationship between teacher job-performance determinants i.e. Organizational Culture, Organizational Structure, and Work Motivation. It was found that path coefficient of organizational culture to work motivation is 0.333 at a significant level of < 0.05 and F = 17.553, where Fcalc.> F1/141= 3.908, at α < 0.05. In addition, path coefficients of organizational culture and work motivation to job-satisfaction are 0.225, and 0.263 respectively at a significant level of < 0.05 and F = 13.224, where Fcalc.> F2/140= 3.061, at α < 0.05. Furthermore, path coefficients of organizational culture, work motivation and job-satisfaction to job-performanc are 0.269, 0.236, and 0.193 respectively at a significant level of < 0.05, and F = 17.261, where Fcalc.> F3/139= 2.669, at α < 0.05. Finally, indirect effect of organizational culture on job-satisfaction and job-peformance through work motivation is 0.087, and 0.078 respectively. It is concluded that the Model suggested fits with data collected, as a result, it can be used for perdicting teacher job-performance, including teacher promotions and feedback for improving teacher performance.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".