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Record W2275414352 · doi:10.5539/ies.v9n3p131

Emotional Intelligence and Its Relation with the Social Skills and Religious Behaviour of Female Students at Dammam University in the Light of Some Variables

2016· article· en· W2275414352 on OpenAlexvenueno aff
Eman Mohammad Reda Ali Al-Tamimi, Naseer Ahmad Al-Khawaldeh

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCarelessnessPsychologyEmotional intelligenceFriendshipAggressionSocial psychologyThe artsSample (material)Developmental psychologyMathematics education

Abstract

fetched live from OpenAlex

<p class="apa">The study has examined the correlation between emotional intelligence, social skills, and religious behavior among university female students, since it had been noticed that there was escalation in the frequency of some behavioral and emotional problems such as vandalism, aggression, social withdrawal, weakness of social relations, patterns of friendship between female students, lack of positive social attributes, indifference and carelessness towards lectures, and frequent absence. The study has followed the quantitative research approach by the emotional intelligence criterion, social skills criterion and religious behavior criterion. The study sample consisted of 338 female students of the university students selected by the purposive sample method from both Islamic Studies and Arabic Language Departments. The study revealed that the average grade for the emotional intelligence among the female university students the Faculty of Arts in Hafar Al-Batin/University of Dammam is high–the arithmetic average on the criterion as a whole reached 3.611. The average grade for the religious behavior among the female university students the Faculty of Arts in Hafar Al-Batin of University of Dammam is high–the arithmetic average on the criterion as a whole reached 4.605.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.385
Teacher spread0.340 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2016
Admission routes1
Has abstractyes

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