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Record W2107204829 · doi:10.2174/1874350100801010001

Cortisol and Cardiac Reactivity in the Context of Sex Discrimination: The Moderating Effects of Mood and Perceived Control

2008· article· en· W2107204829 on OpenAlexafffund
Kimberly Matheson, Ritu Gill, Owen Kelly, Hymie Anisman

Bibliographic record

VenueThe Open Psychology Journal · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsPsychologySadnessAngerStressorHeart rateHostilityMoodBlood pressureArousalContext (archaeology)FeelingReactivity (psychology)Clinical psychologyDevelopmental psychologyInternal medicineSocial psychologyMedicine

Abstract

fetched live from OpenAlex

The high incidence of stressor-related pathologies among stigmatized groups has been associated with experiences of discrimination. The present study demonstrated that following a mood priming manipulation (anger vs. sadness), an acute sex discrimination event influenced women’s (N=61) salivary cortisol levels as well as systolic (SBP) and diastolic (DBP) blood pressure. Among women primed to feel sad, cortisol levels declined over the course of the experimental session, likely reflecting a decline of arousal. However, among those primed to feel angry the cortisol levels were sustained over the session, especially if they perceived the possibility of rectifying their failed status (control). As well, SBP and DBP increased following the discrimination experience irrespective of perceived control. Among women primed to feel angry, feelings of hostility were associated with higher SBP and heart rate. Evidently, sex discrimination affects stress-reactive physiological systems among women, and might thus influence vulnerability to pathology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.042
GPT teacher head0.337
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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

Citations15
Published2008
Admission routes2
Has abstractyes

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