The Future Justification to Adopt Governance System at the Jordan Universities from the Perspective of Educational Experts
Bibliographic record
Abstract
The aim of the study was to reveal the future justification to adopt governance system at the Jordanian Universities from the perspective of educational experts. The study society was the academic staff in the field of education at Al-Balqa Applied University and Jordan University, at the first semester of the academic year 2013-2014. The study sample consisted of 30 academic members. The researcher used the analytical descriptive approach by using Delphi method as an analytical tool for the future justification. The questionnaire for the study consisted of 19 items after verifying its authenticity and approval. The results have revealed that the academic members agreed on the transparency factors and it was 88%. Also, they have agreed on accountability and control and it was (90%). They agreed on the justice and equality factors with a percentage of 94%. According to the results; the study has recommended that review obstacles to apply the concept of university governance which were: The general political climate, the university legislations, the university administration process. The researcher recommended that the concept of university governance and its implications still need more studies have to be conducted using different influential factors. Future directions for research, policy and practices are presented.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".