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Record W2345965789 · doi:10.1017/s1743923x16000131

Do Women and Men Respond Differently to Negative News?

2016· article· en· W2345965789 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

VenuePolitics & Gender · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsPsychologySkin conductanceArousalNeuropsychologySocial psychologyDevelopmental psychologyClinical psychologyMedicineCognitionPsychiatry

Abstract

fetched live from OpenAlex

This article offers a new approach to studying sex differences in responses to negative news, using real-time physiological responses as opposed to self-reports. Measurements of skin conductance and heart rate are used to examine whether there are differences in the extent to which women and men are aroused by and attentive to negative news stories. Like experiments that have relied on postexposure self-reports, we detect no sex differences in arousal in response to negative news stories. However, in contrast to those experiments, we find indications that women are more attentive than men to negative news content. We consider possible reasons for this difference in findings. We also discuss neuropsychological studies that are consistent with our finding of greater attentiveness on the part of women to negative stimuli. Finally, we consider the relationship between our work and evidence in the literature that women consume less news than men.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score1.000

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)0.0040.001

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 head0.112
GPT teacher head0.425
Teacher spread0.312 · 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