Dimensions of the Learning University in Confronting COVID 19 Pandemic Challenges: A Field Study in Saudi Public Universities from a Leadership Perspectives
Bibliographic record
Abstract
The present study aims to investigate the relationship and predictability between the roles of leaders in Saudi public universities in consolidating the dimensions of learning organizations (universities) and their abilities in confronting COVID 19 pandemic challenges. A total of 228 leaders in three Saudi public universities took part in the current study. A questionnaire was designed for collecting data, which consisted of general data, The Dimensions of Learning Organization Questionnaire (DLOQ), and Confronting COVID 19 Pandemic Challenges Scale (CCPCS) developed by the researcher of this study. The results of the study showed a positive relationship between the roles of leaders in Saudi public universities in consolidating the dimensions of learning organizations (universities) and their abilities in confronting COVID 19 pandemic challenges, and that these roles of leaders are good predictors of these abilities. Results also indicate that there are no significant differences in both study scales across gender, age, academic qualifications, and years of work experience. It is recommended to increase the leaders’ roles in the Saudi public universities in consolidating the dimensions of the learning organization, as this has an impact on their abilities in in confronting COVID 19 Pandemic challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".