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Record W2032971871 · doi:10.3200/socp.147.4.325-344

From Emotional Intelligence to Intelligent Choice of Partner

2007· article· en· W2032971871 on OpenAlexaff
Oren Aaron Amitay, Myriam Mongrain

Bibliographic record

VenueThe Journal of Social Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsEmotional intelligencePsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

The authors examined interpersonal correlates of emotional intelligence (EI) in a sample of individuals with a history of depression. The authors focused on potentially adaptive relationship dynamics associated with EI that may help protect these vulnerable individuals from further distress. Participants with high EI, as measured with the Mayer-Salovey-Caruso Emotional Intelligence Test, saw their partners as less hostile, critical, and rejecting in their support styles than did participants with low EI. Partners' own reports mostly corroborated these findings. Unexpectedly, although partners of high EI participants reported offering less active and directive support than did partners of low EI participants, high EI participants perceived their partners as more supportive than did low EI participants. Partners of emotionally intelligent participants also reported being more conscientious and open to experiences, offering some evidence of the stress-buffering hypothesis associated with higher EI.

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)0.010
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.470
Teacher spread0.346 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

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