Anger and shame elicited by discrimination: Moderating role of coping on action endorsements and salivary cortisol
Bibliographic record
Abstract
Abstract Discrimination often elicits anger, and yet group members typically do not take actions to confront their situation. It may be that other emotions that run contrary to action‐taking also arise (e.g., shame), limiting the active expression of anger. Indeed, Study 1 ( N = 36) revealed that, using a failure feedback paradigm, women expressed greater shame when their failure was due to discrimination, compared to a lack of personal merit. In contrast to anger, self‐reported shame was not associated with action‐taking. In Study 2, women ( N = 91) were emotionally primed to feel either anger or shame (vs. a no mood prime control), and the moderating influence of coping styles on the link between emotions, actions, and salivary cortisol levels following discrimination were assessed. Among women primed to feel anger, problem‐focused coping predicted reduced self‐reported shame, lower cortisol reactivity, and greater individualistic confrontational action endorsements. In contrast, priming shame increased cortisol reactivity, but diminished the relation between particular coping styles and their capacity to facilitate action. Findings are discussed in terms of the interactive influence of emotions and coping on responses to discrimination. Copyright © 2008 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".