The Method of Selecting Academic Leaders at Emerging Saudi Universities and its Relationship to Some Variables
Bibliographic record
Abstract
The study aimed to identify the current method used for selecting academic leaders at emerging Saudi universities from the viewpoint of faculty members working there, and whether there is a correlation between the method used and the following variables: job satisfaction, organizational justice, organizational commitment, productivity motivation, and institutional loyalty and affiliation. In order to achieve the goals of the study, the researcher designed a questionnaire that included identifying the method used. The questionnaire consisted of (31) items divided according to the variables mentioned, and it was distributed to the study sample (300 faculty members), randomly chosen from the study community (2382 members). The results showed that there is a correlation between the method used and the variables mentioned which were at an intermediate level, with the exception of the productivity motivation that was at a high level for university professors, despite the fact that the foregoing variables were lower than expected. This made the researcher recommend that the university and the Ministry of Education would review that mechanism and hold conferences and workshops in order to address it before these positive professors suffer from disappointment and job burnout. The study also revealed that there were statistically significant differences at the level of (α = 0.05) in experience in favor of (10) years or more, in the academic rank in favor of (Assistant Professor), and in officiality and contracting in favor of the contracting parties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".