MétaCan
Menu
Back to cohort
Record W2105269589 · doi:10.1037/a0034410

Are narcissists hardy or vulnerable? The role of narcissism in the production of stress-related biomarkers in response to emotional distress.

2013· article· en· W2105269589 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEmotion · 2013
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsNarcissismPsychologyDistressDevelopmental psychologyVulnerability (computing)Clinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Does narcissism provide a source of hardiness or vulnerability in the face of adversity? The present research addressed this question by testing whether narcissism is associated with increased physiological reactivity to emotional distress, among women. Drawing on the "fragile-ego" account, we predicted that narcissists would show a heightened physiological stress profile in response to everyday frustrations. Results supported this prediction; across a 3-day period, highly narcissistic individuals showed elevated output of 2 biomarkers of stress--cortisol and alpha--amylase-to the extent that they experienced negative emotions. In contrast, among those low in narcissism there was no association between these biomarkers and emotions. These findings suggest that narcissists' stress-response systems are particularly sensitive to everyday negative emotions, consistent with the notion that narcissism comes with physiological costs.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.311
Teacher spread0.283 · 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