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Record W2021178079 · doi:10.1177/0013164403261762

The Nature and Measurement of Emotional Intelligence Abilities: Basic Dimensions and Their Relationships with Other Cognitive Ability and Personality Variables

2004· article· en· W2021178079 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducational and Psychological Measurement · 2004
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyPersonalityAlexithymiaCognitionEmotional intelligenceDevelopmental psychologyBig Five personality traitsConstruct (python library)Congruence (geometry)Social psychologyCognitive psychology

Abstract

fetched live from OpenAlex

Dimensions of Emotional Intelligence (EI) were derived, and their place with respect to the cognitive ability and personality domains was examined. A factor analysis of 24 maximum-performance and self-report EI measures administered to an undergraduate sample ( N= 176) yielded five factors: Emotional Congruence, Emotional Independence, Social Perceptiveness, Alexithymia, and Social Confidence. Emotional Congruence had lowcorrelations with four cognitive ability factors and Big Five personality factors, indicating that it may represent either a new psychological construct or a method factor. Social Perceptiveness correlated significantly with cognitive abilities, indicating its place in this domain. The remaining three factors had moderate correlations with various personality dimensions and low correlations with cognitive abilities, indicating that they fall outside the latter domain. On the basis of the present results, only maximum-performance and not self-report measures of EI can be seen as tapping the cognitive ability domain.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.171
GPT teacher head0.352
Teacher spread0.181 · 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