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Record W4411645631 · doi:10.1371/journal.pone.0323938

Multi-region investigation of ‘man’ as default in attitudes

2025· article· en· W4411645631 on OpenAlexaff
Curtis E. Phills, Jeremy K. Miller, Erin Michelle Buchanan, Amanda Williams, Chanel Meyers, Elizabeth R. Brown, Janis Zickfeld, Selina Volsa, Stefan Stieger, Elisabeth Oberzaucher, Vinka Mlakic, Martin R. Vasilev, İlker Dalḡar, Sami Çoksan, Sinem Söylemez, Çağlar Solak, Asil Ali Özdoğru, Belemir Çoktok, Chun‐Chia Kung, Panita Suavansri, Harry Manley, Sara Álvarez Solas, Ivan Ropovik, Gabriel Baník, Peter Babinčák, Matúš Adamkovič, Pavol Kačmár, Monika Hricová, Jozef Bavoľár, Lisa Li, Fei Gao, Zhong Chen, Vanja Ković, Vasilije Gvozdenović, Patrí­cia Arriaga, Katarzyna Filip, Krystian Barzykowski, Sylwia Adamus, Gerit Pfuhl, Sarah E. Martiny, Kristoffer Klevjer, Frederike S. Woelfert, Christian K. Tamnes, Jonas R. Kunst, Max Korbmacher, Margaret Messiah Singh, Sraddha Pradhan, Noorshama Parveen, Arti Parganiha, Babita Pande, Pratibha Kujur, Priyanka Chandel, Niv Reggev, Aviv Mokady, Μαριέττα Παπαδάτου-Παστού, Roxane Schnepper, Jan Philipp Röer, Tilli Ripp, Ekaterina Pronizius, Claus Lamm, Martin Voracek, Jerome Olsen, Janina Enachescu, Carlota Batres, Daniel Storage, Carmel Levitan, Manyu Li, Leigh Ann Vaughn, William J. Chopik, Kathleen Schmidt, Peter Robert Mallik, Savannah C Lewis, Brynna Leach, Brianna Jurosic, David Moreau, Izuchukwu L. G. Ndukaihe, Nwadiogo Chisom Arinze, Steve M. J. Janssen, Alicia Foo, Chrystalle B. Y. Tan, Glenn Patrick Williams, Danny Riis, Bethany M. Lane, Dermot Lynott, Thomas Rhys Evans, Miroslav Sirota, Dawn Liu Holford, Kaitlyn M. Werner, Kelly Wang, Marina Milyavskaya, Ian D. Stephen, Robert M. Ross, Andrew Roberts, Omid Ghasemi, Niklas K. Steffens, Kim Peters, Barnaby Dixson, Marco Antônio Corrêa Varella, Jaroslava Varella Valentová, Anthonieta Looman Mafra, Rafael Ming Chi Santos Hsu, Yago Luksevicius Moraes, Luana Oliveira da Silva, Caio Santos Alves da Silva, Mai Helmy, Mariah Balderrama, Ali H. Al‐Hoorie, T. J. McGee, Zahir Vally, Attila Szuts, Patrick S. Forscher, Pablo Bernabeu, Balázs Aczél, Anna Szabelska, Sau-Chin Chen, Christopher R. Chartier, Zoltán Kekecs

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCarleton UniversityWestern UniversityRegional Municipality of Waterloo
FundersAustralian Research CouncilVedecká Grantová Agentúra MŠVVaŠ SR a SAVFundação para a Ciência e a TecnologiaFundação de Amparo à Pesquisa do Estado de São PauloAgentúra na Podporu Výskumu a VývojaNarodowym Centrum NaukiLeverhulme TrustJohn Templeton Foundation
KeywordsPrejudice (legal term)CategorizationSocial psychologyModerationWhite (mutation)PsychologyEthnic groupPolitical science

Abstract

fetched live from OpenAlex

Previous research has studied the extent to which men are the default members of social groups in terms of memory, categorization, and stereotyping, but not attitudes which is critical because of attitudes' relationship to behavior. Results from our survey (N > 5000) collected via a globally distributed laboratory network in over 40 regions demonstrated that attitudes toward Black people and politicians had a stronger relationship with attitudes toward the men rather than the women of the group. However, attitudes toward White people had a stronger relationship with attitudes toward White women than White men, whereas attitudes toward East Asian people, police officers, and criminals did not have a stronger relationship with attitudes toward either the men or women of each respective group. Regional agreement with traditional gender roles was explored as a potential moderator. These findings have implications for understanding the unique forms of prejudice women face around the world.

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)0.003
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.125
GPT teacher head0.364
Teacher spread0.239 · 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
Published2025
Admission routes1
Has abstractyes

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