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Record W2098276566 · doi:10.1177/0734282914550381

Self-Report Assessments of Emotional Competencies

2014· article· en· W2098276566 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

VenueJournal of Psychoeducational Assessment · 2014
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsWestern University
FundersSwinburne University of Technology
KeywordsPsychologyCompetence (human resources)Construct validityPersonalitySocial psychologyApplied psychologyPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

This Special Issue of the Journal of Psychoeducational Assessment offers a critical appraisal of the validity, applied utility, and limitations of self-report assessments of emotional competencies. Using self-concept theory as an integrative theoretical framework, this introductory editorial highlights key methodological and validity issues raised in the contributing articles: (a) distinction between emotional competence self-perceptions and objectively measured abilities, (b) effects of response biases and respondents’ age on the psychometric properties of self-reports, (c) importance of adopting a multi-dimensional assessment strategy, and (d) various aspects of construct validity (conceptual definitions and paradigms, gender differences, relationships with basic personality, mechanisms and scope of prediction). The added value of conceptualizing emotional competence self-reports as self-concepts (as proposed in this article) is illustrated in the discussion of practical implications, outstanding questions, and directions for future research on the meaning and uses of these assessments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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

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 head0.045
GPT teacher head0.445
Teacher spread0.400 · 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