ReviewPsychonomic bulletin & review2023
Structure learning principles of stereotype change.
Review in Psychonomic bulletin & review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Stereotypic beliefs dominate reversal learning.Scientific reports · 2026Article
- A simple threshold captures the social learning of conventions.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Lack of group-to-individual generalizability in pseudocontingencies.Scientific reports · 2026Article
- Increased complexity of social category markers leads to diverse rule-based categorizations and reduced intergroup bias.Proceedings. Biological sciences · 2025Article
- Humans learn generalizable representations through efficient coding.Nature communications · 2025Article
- Islamic law perspectives and social experiences on stigma toward disabled people in Indonesia.Frontiers in sociology · 2025Article
- The Relative Contributions of Traits and Contexts on Social Network Learning.Open mind : discoveries in cognitive science · 2025Article
- Facial misfits accelerate stereotype-based associative learning.Scientific reports · 2024Article
- Asymmetric cognitive learning mechanisms underlying the persistence of intergroup bias.Communications psychology · 2024Article
- The Role of Predictions, Their Confirmation, and Reward in Maintaining the Self-Concept.Frontiers in human neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Why, when, and how do stereotypes change? This paper develops a computational account based on the principles of structure learning: stereotypes are governed by probabilistic beliefs about the assignment of individuals to groups. Two aspects of this account are particularly important. First, groups are flexibly constructed based on the distribution of traits across individuals; groups are not fixed, nor are they assumed to map on to categories we have to provide to the model. This allows the model to explain the phenomena of group discovery and subtyping, whereby deviant individuals are segregated from a group, thus protecting the group's stereotype. Second, groups are hierarchically structured, such that groups can be nested. This allows the model to explain the phenomenon of subgrouping, whereby a collection of deviant individuals is organized into a refinement of the superordinate group. The structure learning account also sheds light on several factors that determine stereotype change, including perceived group variability, individual typicality, cognitive load, and sample size.
Indexed as
Identifiers
36973602What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.