The Impact of Authentic Leadership on Smart Organization in Jordan Telecom Group (Orange)
Bibliographic record
Abstract
The study aims at identifying the concept of Authentic Leadership “AL” and its impact on the Smart Organization “SO” in Jordan Telecom Group (Orange) “JTG”. The study population comprises all the members of the supervisory and directive management in JTG, which includes (737) members. The sample representing the population of (737) members is (250) members and in order to ensure population representation, (300) questionnaires were distributed by e-mail. Number of (292) questionnaires were retrieved. The Statistical Package of Social Sciences (SPSS) was used. The results of the study showed that there is a significant impact of Authentic Leadership with its dimensions on Smart Organization with its combined dimensions at level (P ≤ 0.05) at JTG in Jordan; and the results showed also that there is a significant impact of Authentic Leadership with its dimensions on Understanding the Environment at level (P ≤ 0.05) at JTG in Jordan. Finally, the researcher provides the following recommendations: JTG is recommended to provide professionals and specialists who conduct the needed proper assessment and analysis of the uncertainties’ effects on the company’s business; JTG is advised to review its policies and plans related to the adopted methods of using and reallocating its human resources and their corresponding capabilities.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".