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Record W1602099217 · doi:10.2189/asqu.51.1.1

Emotional Intelligence, Cognitive Intelligence, and Job Performance

2006· article· en· W1602099217 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

VenueAdministrative Science Quarterly · 2006
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmotional intelligencePsychologyOrganizational citizenship behaviorTask (project management)CognitionHuman intelligenceJob performanceCognitive psychologySocial psychologyTest (biology)Job analysisApplied psychologyOrganizational commitmentManagementDevelopmental psychologyJob satisfaction

Abstract

fetched live from OpenAlex

This paper examines how emotional intelligence and cognitive intelligence are associated with job performance. We develop and test a compensatory model that posits that the association between emotional intelligence and job performance becomes more positive as cognitive intelligence decreases. We report the results of a study in which employees completed tests of emotional intelligence and cognitive intelligence, and their task performance and organizational citizenship behavior were assessed by their supervisors. Hypotheses from the model were supported for task performance and organizational citizenship behavior directed at the organization, but not for organizational citizenship behavior directed at individuals. We discuss the theoretical implications and managerial ramifications of our model and findings.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.367
Teacher spread0.307 · 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