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Record W4391030363 · doi:10.1027/1614-0001/a000417

Validation of the Short Dark Tetrad (SD4) in Persian

2024· article· en· W4391030363 on OpenAlex
Kaveh Qaderi Bagajan, Matthias Ziegler, Mehdi Soleimani, Delroy L. Paulhus, Zahra Asl Soleimani, Mohammadreza Kordbagheri, Leila Alavinejad, Hamid Lorvand Amiri, Vida Yousefi Asl, Sepideh Hoseini, Hadi Qaderi Bagajan

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 Individual Differences · 2024
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMachiavellianismPsychopathyPsychologyNarcissismNomological networkDark triadPersonalityBig Five personality traitsConfirmatory factor analysisStructural equation modelingPersianSocial psychologyStatistics

Abstract

fetched live from OpenAlex

Abstract: The Short Dark Tetrad of Personality (SD4) is a self-report instrument for screening individuals with dark personality traits, including narcissism, Machiavellianism, psychopathy, and sadism. In the present study, we examined the psychometric properties of the Persian version in an Iranian sample. After translating the instrument, we conducted a large online survey that included 1,696 participants (67% female), aged 18–60 years. We performed a series of confirmatory factor analyses and examined the nomological network to validate the instrument. After assessing five competing structural models, the four-factor model showed the best fit based on standard goodness-of-fit indices. The sub-scales also showed coherent links with risk-taking and pathological personality traits. We conclude that the Persian SD4 has a distinct four-factor structure with adequate reliability and validity. Therefore, it can be used to measure dark personality traits in Farsi-speaking samples.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.744

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 science0.0010.000
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 head0.071
GPT teacher head0.355
Teacher spread0.284 · 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