Trends of Administrative and Academic Leadership towards Achieving Governance, An Applied study in Official Jordanian Universities in Southern Jordan
Bibliographic record
Abstract
is study aimed at analyzing the trends of administrative and academic leaders towards achieving governance in the official Jordanian universities in southern Jordan. To achieve the objectives of the study, a questionnaire was developed covering the study variables, it was distributed to the study population consisting of administrative and academic leaders in three official universities in southern Jordan, which is Mutah, Al-Hussein Bin Talal, and Tafila Technical), who were (904) employees, the study sample was selected in a random, stratified proportional method of (452) respondents forming (50%) of the study population. Descriptive and analytical statistical methods were used, using the statistical package (SPSS.16), the study reached a set of results including the following: That the Mean of the respondents 'perceptions of the dimensions of the administrative and academic leadership trends in public universities in southern Jordan had a high degree, and that the Mean of the respondents' perceptions of the governance dimensions in public universities in southern Jordan had a high degree. The study results showed a statistically significant positive relationship between the independent variable (leadership trends) and its various dimensions and the dependent variable (governance) and its various dimensions. The study revealed many recommendations, including: Paying attention to continuous training of leaders on understanding administrative activity, especially in the field of leadership behavior in universities to activate the role of leaders in these universities, spreading and strengthening governance culture among their employees as it will be reflected in the decisions of the institution, in turn on its 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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".