The Relationship between Practicing Knowledge Management Processes and the Effectiveness of Administrative Decisions Made by Schools’ Principals in Ma’an Governorate
Bibliographic record
Abstract
This study aims at determining the level of practicing knowledge management processes and the effectiveness level of administrative decisions made by the schools’ principals in Ma’an Governorate, as well as determining the nature of the relationship between practicing knowledge management processes and the effectiveness level of making administrative decisions. A sample consisting of 120 school principals was randomly chosen.The study found that the levels of practicing knowledge management by the school principals in Ma’an Governorate were all high and ranged between 4.28-4.52. The results also showed that the arithmetic means for the effectiveness level of the administrative decisions made by school principals in Ma’an Governorate ranged between 4.33-4.75 with high practicing level. Moreover, there is a statistically significant relationship between the effectiveness level of administrative decision-making on the one hand and the fields of knowledge management processes on the other hand. There are also statistically significant differences between the arithmetic means of the (High Diploma) estimates on the one hand, and the arithmetic means of the (Bachelor degree) estimates on the other hand, regarding the field “transferring and using knowledge” in favor of the (High Diploma). The same goes for the (Bachelor degree) estimates on the one hand, and the (Master degree) estimates on the other hand in favor of the (Master degree).
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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 | 0.008 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".