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Record W1988021599 · doi:10.1177/0146167205279906

Responses to Discrimination: The Role of Emotion and Expectations for Emotional Regulation

2005· article· en· W1988021599 on OpenAlexaff
Ritu Gill, Kimberly Matheson

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologySocial psychologyStatus quoAction (physics)NormativePerceptionCollective actionEmotional expressionAngerPolitics

Abstract

fetched live from OpenAlex

The present study examined the role of emotion in women's perceptions of discrimination and their endorsement of behavioral responses to change the status quo. In an experimental simulation involving a situation of sex discrimination, women (N = 108) were primed to experience a particular emotion (sad, angry, control condition) and were subsequently instructed to either suppress or express (or neither) their emotional responses. Women primed to feel sad and told to suppress their emotions reported the least discrimination, whereas angered women who were permitted to express themselves reported the greatest discrimination. Furthermore, when encouraged to express their emotions, women primed to feel sad were more likely to endorse normative actions to rectify the situation, whereas women induced to feel angry were more likely to endorse collective actions to change the status quo. These findings have implications for the role of emotions and expectations regarding their expression on collective action taking.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.049
GPT teacher head0.383
Teacher spread0.334 · 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

Citations54
Published2005
Admission routes1
Has abstractyes

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