Emotional Intelligence and Transformational Leadership Style Empirical Research on Public Schools in Jordan
Bibliographic record
Abstract
The aim of this study is to investigate the relationship between emotional intelligence (EI) and transformational leadership (TL) style in public schools in Amman, Jordan. A sample consisting of 250 teachers was randomly selected to collect data on their managers’ EI competencies, which are self-awareness (SEA), self-management (SEM), social awareness (SOA), and relationship management (REM), and their TL behaviours using a questionnaire developed based on the literature for the purpose of the current study. All the questionnaires were returned completed and valid for statistical analysis. Four hypotheses were put forward by the study, in which EI was postulated to exert an impact on four dimensions of TL style, namely idealized influence (IDI), inspirational motivation (INM), intellectual stimulation (INS), and individualized consideration (INC). The study deduced a significant and positive effect of EI on all the dimensions of TL. A key contribution of this study is the finding that leaders need not only competencies to transform their subordinates but also a sense of emotional intelligence. Following these results, the implications of the study were derived. One of the most important recommendations indicated that managers have to be trained to acquire emotional intelligence skills.
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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 | 0.002 |
| 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 | 0.000 |
| 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".