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Record W7120158765 · doi:10.1353/jip.00031

Examining the Psychometric Properties of an English Translation of the Shortened Inferiority and Superiority Complex Scales

2025· article· en· W7120158765 on OpenAlexaboutno aff
Đorđe Čekrlija, Julie Aitken Schermer, Jhanvi Patel

Bibliographic record

Venue˜The œjournal of individual psychology · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsAdlerianFacet (psychology)Scale (ratio)Set (abstract data type)PersonalityConfirmatory factor analysisPsychometrics

Abstract

fetched live from OpenAlex

Abstract: The present study set out to assess the psychometric properties of the English translation of the short Inferiority Complex (COMPIN-10) and Superiority Complex (SUCOMP-10) scales, which are based on Adlerian Individual Psychology and originally developed in Serbian, on a Canadian sample. Students ( N = 565) completed the shortened inferiority and superiority complex scales and the depression facet scale from a Big Five personality inventory. Both scales showed approximated normal distributions and had good reliability. The results of the confirmatory factor analysis confirmed the unidimensional structure for both scales. Results also showed that the depression scale scores were positively correlated with the inferiority complex scores and negatively with the superiority complex scores. Findings support using the shortened inferiority and superiority complex scales in English.

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 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)0.019
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.500
GPT teacher head0.449
Teacher spread0.051 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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