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Record W2139815911 · doi:10.1080/00223891.2014.989367

The Core Self-Evaluation Scale: Psychometric Properties of the German Version in a Representative Sample

2014· article· en· W2139815911 on OpenAlex
Markus Zenger, Annett Körner, Günter W. Maier, Andreas Hinz, Yve Stöbel‐Richter, Elmar Brähler, Anja Hilbert

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 Personality Assessment · 2014
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisPsychometricsGermanClinical psychologyStructural equation modelingPersonalityPopulationSample (material)Scale (ratio)AnxietyConstruct validitySocial psychologyStatisticsPsychiatryDemography

Abstract

fetched live from OpenAlex

The Core Self-Evaluation Scale (CSES) is an economical self-reporting instrument that assesses fundamental evaluations of self-worthiness and capabilities. The broad aims of this study were to test the CSES's psychometric properties. The study is based on a representative survey of the German general population. Confirmatory factor analyses were conducted for different models with 1, 2, and 4 latent factors. The CSES was found to be reliable and valid, as it correlated as expected with measures of depression, anxiety, quality of life, self-report health status, and pain. A 2-factor model with 2 related factors (r = -.62) showed the best model fit. Furthermore, the CSES was measurement invariant across gender and age. In general, males had higher values of positive self-evaluations and lower negative self-evaluations than females. It is concluded that the CSES is a useful tool for assessing resource-oriented personality constructs.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.029
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.086
GPT teacher head0.405
Teacher spread0.320 · 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