Social categorization and memory for in-group and out-group behavior.
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In general, people retain information in a more detailed fashion, remember more positive information, and are more forgiving of behaviors for ingroup compared to outgroup members.
“In general, people retain information in a more detailed fashion, remember more positive information, and are more forgiving of behaviors for ingroup compared to outgroup members.102–104”
From Reducing Racial Bias Among Health Care Providers: Lessons from Social-Cognitive Psychology (2007) · cites this paper as [103]
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The need to belong: Desire for interpersonal attachments as a fundamental human motivation.
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Reducing Racial Bias Among Health Care Providers: Lessons from Social-Cognitive Psychology
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Extending the Benefits of Recategorization: Evaluations, Self-Disclosure, and Helping
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Group Representations and Intergroup Bias: Positive Affect, Similarity, and Group Size
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A Negativity Bias in Reframing Shapes Political Preferences Even in Partisan Contexts
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- Authors
- Howard, J. W., & Rothbart, M.
- Affiliations
- University of Oregon (US)
- Venue
- Journal of Personality and Social Psychology
- Published
- 1980-02
- Volume
- 38
- Issue
- 2
- Pages
- 301-310
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W1965303159
- Cited by
- 350
- References
- 13
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 8 · 2023: 11 · 2022: 7 · 2021: 10 · 2020: 14 · 2019: 17 · 2018: 7 · 2017: 8 · 2016: 9 · 2015: 8 · 2014: 14 · 2013: 8 · 2012: 9
- FWCI
- 22.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Personality and Social Psychology (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Social Psychology › Death Anxiety and Social Exclusion
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- social categorization, memory, social categorization theory
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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