Group‐Based Shame and Guilt: Emerging Directions in Research
Bibliographic record
Abstract
Abstract Research on the role of emotion in social identity, group processes, and intergroup conflict is burgeoning. This paper examines recent research on group‐based shame and guilt and describes important themes in this research. Guilt and shame are distinguished by different appraisals and motivations in intergroup contexts. Group‐based shame is associated with threats to group‐image and motivations to protect and repair that image. In contrast, group‐based guilt is associated with efforts to repair and apologize for ingroup wrongdoing. Current research is expanding in several important directions. First, the scope of emotions is expanding beyond that of shame and guilt to consider the roles of emotions such as ingroup‐directed anger in situations that may also provoke group‐based shame and guilt. Second, people’s motivations to avoid feeling group‐based shame and guilt are becoming better understood, particularly in relation to different aspects of social identification. Finally, we argue that dynamic processes in emotion expression and experience, particularly due to the relation between perpetrator and victim groups, are an important future direction in research on group‐based shame and guilt.
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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 | 0.029 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".