Role of Zarqa University in Improving the Quality of the Services Provided to the Local Community in Zarqa Governorate
Bibliographic record
Abstract
The study aimed to identify the role of Zarqa university in improving the quality of the services provided to the local community in Zarqa governorate. The study also sought to identify the degree of the university's interest in the quality of its services provided to the local community from the perspective of its employees, and have been using the scientific method, which combines the descriptive method and analytical method, so the researcher designed a questionnaire for this purpose, based on some previous studies related to the study, and the questionnaire included in its final form on (45) paragraph, and was test the sincerity of the instrument and its stability, and the stability coefficient of the total instrument is (0. 867). The study was conducted on the members of the faculty and administrative staff at the Zarqa University (580), due to the study population size is large, the researcher resorted to select a stratified random sample with percentage (25%) of the total study population, where the final sample is (98) member of faculty and administrative. The study found a number of results was the most important: that there were no statistically significant differences at the of significance level (≥ α 0.05), between the responses of the employees of Zarqa University about the role of Zarqa university in improving the quality of the services provided to the local community in Zarqa governorate attributed to some personal and functional characteristics represented by (gender, specialty of faculty, Scientific qualification, and experience years).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| 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".