Presenting of Indifference Management Model of Education System in Ardabil Province Using Structural Equation Modeling
Bibliographic record
Abstract
The purpose of the present study is to investigate indifference management structural model in education system of Ardabil Province. The research method was integration study using Alli modeling. Statistical society of research was 420 assistant professors of educational science, managers and deputies of Ardabil’ second period of high schools that 383 individuals were selected by simple random sampling. The data collection tool was researcher-made questionnaire. Face and content validity of the questionnaire was confirmed by experts and its Cronbach’s alpha coefficient was obtained as of 0/80. In order to investigate hypothesizes of research, obtained data were transferred to LISREL software to fit Alli model of structural equation and then were analyzed. The obtained findings of the statistical analysis showed that behavior and performance of manager indirectly has a meaningful impact on indifference management variable through employee’ empowerment variables, job satisfaction of employee, organization’s culture, organizational climate and employee’ perception of the organization. Goodness of fit index (GFI) 0/92 and root mean square of residuals latent variables model was RMSEA=0/045. Therefore, the model has a good fit and has a great ability to measure main variables of research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".