Analyzing the Relationship between Personnel's Education and Psychological Competence on Quality of Service: The Mediation Role of Organization Commitment in Ministry of the Interior
Bibliographic record
Abstract
The goal of the present paper is to analyze the effect of personnel's education and psychological competence on quality of service. The mediation role of organizational competence in Ministry of the Interior is of descriptive-correlational method. To do that, the standard questionnaire psychological competence by Spriters (1995), personnel education and quality of service by Deher (2015) and organizational commitment by Alen and Mier (1990) were used. The statistical population of the research includes all personnel of Ministry of the Interior which are 1600 subjects. Based on Cochran's formula, 3100 subjects were selected randomly. In order to analyze data the Pearson's correlation test and structural equation of data analysis were used by SPSS and AMOS software. The findings of the research indicate that personnel's education has a positive effect on organizational competence and quality of service (with Alpha level of 0.05). Moreover, the psychological competence is positively affect the quality of service (with Alpha level of 0.05) and organizational commitment affect the quality of service. Finally, it was revealed that the personnel training through organizational commitment affect the quality of service. But, psychological competence does not affect the quality of service through organizational commitment. Moreover, psychological competence does not affect the organizational commitment. The significance levelof the model turned out to be more than the first type error (0.05). This shows that the significant adaption of the estimated model with the present research model. Furthermore, the AGFI and GFI indicators are more than the estimated value (0.9). These indicators show that the model has a capability in estimating the ratio of each factor.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".