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Record W653409167

Novel Self-categorization Overrides Racial Bias: A Multi-level Approach to Intergroup Perception and Evaluation

2009· dissertation· en· W653409167 on OpenAlexvenueno aff
Jay Joseph Van Bavel

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsCategorizationIngroups and outgroupsPsychologySocial psychologyPrejudice (legal term)PerceptionSocial perceptionIn-group favoritismSocial groupCognitive psychologySocial identity theoryDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

People engage in a constant and reflexive process of categorizing others according to their race, gender, age or other salient social category. Decades of research have shown that social categorization often elicits stereotypes, prejudice, and discrimination. Social perception is complicated by the fact that people have multiple social identities and self-categorization with these identities can shift from one situation to another, coloring perceptions and evaluations of the self and others. This dissertation provides evidence that self-categorization with a novel group can override ostensible stable and pervasive racial biases in memory and evaluation and examines the neural substrates that mediate these processes. Experiment 1 shows that self-categorization with a novel mixed-race group elicited liking for ingroup members, regardless of race. This preference for ingroup members was mediated by the orbitofrontal cortex – a region of the brain linked to subjective valuation. Participants in novel groups also had greater fusiform and amygdala activity to novel ingroup members, suggesting that these regions are sensitive to the current self-categorization rather than features associated with race. Experiment 2 shows that preferences for ingroup members are evoked rapidly and spontaneously, regardless of race, indicating that ingroup bias can override automatic racial bias. Experiment 3 provides evidence that preferences for ingroup members are driven by ingroup bias rather than outgroup derogation. Experiment 4 shows that self-categorization increases memory for ingroup members eliminating the own-race memory bias. Experiment 5 provides direct evidence that fusiform activity to ingroup members is associated with superior memory for ingroup members. This study also shows greater amygdala activity to Black than White faces who are unaffiliated with either the ingroup or outgroup, suggesting that social categorization is flexible, shifting from group membership to race within a given social context. These five experiments illustrate that social perception and evaluation are sensitive to the current self-categorization – however minimal – and characterized by ingroup bias. This research also offers a relatively simple approach for erasing several pervasive racial biases. This multi-level approach extends several theories of intergroup perception and evaluation by making explicit links between self-categorization, neural processes, and social perception and evaluation.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicSocial and Intergroup PsychologyFrench-language works237,207