MétaCan
Menu
Back to cohort
Record W2410611721 · doi:10.5267/j.msl.2016.5.005

The relationship between emotional intelligence, self-esteem, gender and educational success

2016· article· en· W2410611721 on OpenAlexvenueno aff
Mina Rahimi

Bibliographic record

VenueManagement Science Letters · 2016
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmotional intelligencePsychologySelf-esteemSocial psychologyApplied psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Identifying factors that contribute to academic achievement is important.Some studies suggest a direct correlation between emotional intelligence, self-esteem and academic achievement, but others disagree about any direct relationship.This study investigates the relationship between emotional intelligence, self-esteem and academic achievement.The sample consists of 300 university students who were selected through random sampling.Bar-on emotional Intelligence questionnaire and self-esteem test pop as well as the mean scores of students were used as academic achievement.To analyze research data, descriptive and inferential statistics were used.The results of data analysis show that emotional intelligence and self-esteem had no significant relationship with achievement.The findings also show that emotional intelligence was not different between male and female students, but the self-esteem of female students was more than male students.Therefore in considering effective factors in academic achievement just psychological constructs such as emotional intelligence, self-esteem cannot be stressed.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.360
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueManagement Science LettersSame topicHealth and Well-being StudiesFrench-language works237,207