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Record W2941688249 · doi:10.1080/15298868.2019.1598892

State and trait narcissism predict everyday helping

2019· article· en· W2941688249 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

VenueSelf and Identity · 2019
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsWilfrid Laurier UniversityUniversity of Toronto
Fundersnot available
KeywordsNarcissismTraitPsychologySocial psychologyState (computer science)Cognitive psychology

Abstract

fetched live from OpenAlex

Though grandiose narcissism may seem incompatible with prosocial behavior, evidence of how they relate is mixed. We extend research on this relation by (1) assessing everyday helping, (2) distinguishing narcissistic admiration and rivalry, and (3) assessing state narcissism. Using daily diary methodology and multilevel modeling (N = 380; total observations = 4292), we assess trait narcissism (grandiose, admiration and rivalry), state narcissism, and daily helping over 14 days. Trait grandiose narcissism positively predicted helping but narcissistic rivalry predicted it negatively. State narcissism also positively predicted helping: Participants reported more helping on days they felt more narcissistic. Mood, however, interacted with state narcissism: state narcissism predicted greater helping when daily mood was low but not high.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.311
Teacher spread0.294 · 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