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Record W3130136983 · doi:10.1027/1015-5759/a000634

Gender Differences or Gender Bias?

2021· article· en· W3130136983 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

VenueEuropean Journal of Psychological Assessment · 2021
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsQueen's UniversityLawson Health Research InstituteWestern University
Fundersnot available
KeywordsPsychologyDifferential item functioningItem response theoryTraitPleasureSadistic personality disorderPsychometricsSocial psychologyPersonalityDevelopmental psychologyClinical psychologyPersonality disorders

Abstract

fetched live from OpenAlex

Abstract. Sadism, defined by the infliction of pain and suffering on others for pleasure or subjugation, has recently garnered substantial attention in the psychological research literature. The Assessment of Sadistic Personality (ASP) was developed to measure levels of everyday sadism and has been shown to possess excellent reliability and validity using classical test theory methods. However, it is not known how well ASP items discriminate between respondents of different trait levels, or which Likert categories are endorsed by persons of various trait levels. Additionally, individual items should be evaluated to ensure that men and women of similar levels of sadism have an equal probability of response endorsement. The purpose of this research was to apply item response theory (IRT) and differential item functioning (DIF) to investigate item properties of the ASP across its three translations: English, Polish, and Italian. Overall, the results of the IRT analysis showed that with the exception of Item 9, the ASP demonstrated sound item properties. The DIF rate analyses identified two items from each questionnaire that were of practical significance across gender. Implications of these results are discussed.

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)0.002
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 score0.671
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0350.000

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 head0.377
GPT teacher head0.457
Teacher spread0.080 · 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