MétaCan
Menu
Back to cohort
Record W4404837772 · doi:10.1016/j.paid.2024.112973

Testing the distinction between sadism and psychopathy: A metanalysis

2024· article· en· W4404837772 on OpenAlexaff
Bruno Bonfá-Araújo, Gisele Magarotto Machado, Ariela Raissa Lima‐Costa, Fernanda Otoni, Mahnoor Nadeem, Peter K. Jonason

Bibliographic record

VenuePersonality and Individual Differences · 2024
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyPsychopathyAntisocial personality disorderPsychoanalysisPersonalityPoison controlInjury prevention

Abstract

fetched live from OpenAlex

The relationships among the Dark Triad (DT) traits—Machiavellianism, narcissism, and psychopathy—are well-established in psychological literature. However, with the inclusion of everyday sadism in the proposed Dark Tetrad, it is important to determine whether sadism adds significant explanatory power beyond psychopathy, especially given its high correlation. In this study, we examined whether sadism contributed unique variance over psychopathy in studies where both traits were assessed. A review of PubMed, Google Scholar, and ScienceDirect yielded 185 studies meeting our inclusion criteria, comprising 104,452 participants. We analyzed sample characteristics, including type, size, gender distribution, age, and key correlates such as narcissism, Machiavellianism, the Big Five, and Honesty-Humility. Our results indicate a substantial overlap between sadism and psychopathy, with both traits being strongly related to the other DT traits and showing no correlation with Openness. These findings highlight the need for future research to account for this overlap when interpreting the relationships between sadism, psychopathy, and related psychological 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.

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)0.001
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 score0.322
Threshold uncertainty score0.764

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 studies0.0000.001
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 head0.184
GPT teacher head0.359
Teacher spread0.175 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePersonality and Individual DifferencesSame topicPersonality Traits and PsychologyFrench-language works237,207