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Record W4321495723 · doi:10.1177/13684302231153802

Same view, different lens: How intersectional identities reduce Americans’ stereotypes of threat regarding Arab and Black men

2023· article· en· W4321495723 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGroup Processes & Intergroup Relations · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCégep Marie-VictorinUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyHostilityIdentity (music)Stereotype (UML)Social psychologyStereotype threatPerceptionBlack womenGender studiesSociology

Abstract

fetched live from OpenAlex

Because Black and Arab men may be stereotyped as hostile in different ways (i.e., physical vs. ideological), this study assessed whether an old age identity versus gay identity would reduce stereotypes related to hostility for Black and Arab men differently. We assessed whether the addition of an old age identity reduces hostile stereotype content more for Black men than for Arab men. In line with our hypothesis, an old age identity resulted in participants reporting fewer hostile stereotypes for Black men, but not for Arab men. We also assessed whether a gay identity reduces hostile stereotype content in the same way for Black and Arab men. As expected, a gay identity resulted in participants reporting fewer hostile stereotypes for both male groups. The present study demonstrates the importance of considering intersecting identities in person perception and highlights the unique challenges faced by men belonging to these intersecting groups.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

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

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 head0.045
GPT teacher head0.322
Teacher spread0.277 · 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