The Impact of Electronic Management on the Employees' Performance Field Study on the Public Organizations and Governance in Jerash Governorate
Bibliographic record
Abstract
The study aimed at knowing the impact of Electronic management on the employees' performance- a field study that was applied on the public organization in Jerash Governorate, the researcher followed the descriptive analytical approach, then analyze the relationship between the independent variable (Electronic management) and the dependent variable (employees' performance), aiming at knowing the impact of the independent variable on the dependent variable. In order to achieve the study goal, a 24 paragraphs questionnaire was developed to gather the initial information from the study population, and then analyze these information using SPSS V 22. The study found that the requirements of Electronic management are available in the public governance in Jerash, and the results showed a significant positive relationship between all dimensions of Electronic management and employees' performance. The study provided a group of recommendations to speed up adopting the electronic management in the public governance in Jordan specially in Jerash; one of the most important recommendations was the continuous follow up on applying the concepts of Electronic management in the different public, private, and service governance in order to keep up with the challenges and development and focus on accessibility and globalization and providing the possible services, within a comprehensive functional model to satisfy the widest slice of the community as soon as possible and in the least cost possible.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".