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Record W4405319593 · doi:10.1037/pspa0000433

Prejudice and stereotypes at regional and individual levels: Related but distinct.

2024· article· en· W4405319593 on OpenAlexafffund
Jennifer Suliteanu, Eugene K. Ofosu, Eric Hehman

Bibliographic record

VenueJournal of Personality and Social Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrejudice (legal term)PsycINFOPsychologySocial psychologyStereotype (UML)Construct (python library)Social perceptionVariation (astronomy)Similarity (geometry)PerceptionMEDLINE

Abstract

fetched live from OpenAlex

Exploring how psychological constructs and their outcomes vary across geographic regions is a rapidly expanding area of research, yet fundamental questions remain. Can constructs designed to describe individual variation in attitudes be interpreted in the same way when aggregated to regional levels? To what extent are they related or distinct? We tested the relationship between individual and regional attitudes across four studies in the domain of intergroup attitudes. Participants reported explicit prejudices and stereotypes toward 14 different social groups, and incorporating data from Project Implicit, we compared the characteristics of regional and individual operationalizations of prejudice. Further, we tested whether attitudes related to one another in the same way across levels using representational similarity analysis. Drawing from construct validity theory, we find evidence that regional prejudice is an emergent property of individual attitudes, to which it is related but distinct. These findings contextualize stereotype and prejudice constructs in regional analyses in psychology. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.727
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.238
GPT teacher head0.428
Teacher spread0.189 · 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 teacher head, 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

Citations2
Published2024
Admission routes2
Has abstractyes

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