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Record W2509974002 · doi:10.5539/ibr.v9n9p168

Emotional Intelligence and Transformational Leadership Style Empirical Research on Public Schools in Jordan

2016· article· en· W2509974002 on OpenAlexvenueno aff
Mohammad Faleh Ahmmad Hunitie

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipEmotional intelligencePsychologyLeadership styleStyle (visual arts)Empirical researchSocial consciousnessSocial psychologyApplied psychologyPolitical science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.004

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.

Opus teacher head0.585
GPT teacher head0.535
Teacher spread0.050 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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