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Record W4401688049 · doi:10.1073/pnas.2401919121

Is gender primacy universal?

2024· article· en· W4401688049 on OpenAlexaff
Ashley E. Martin, Diego Guevara Beltrán, Jeremy Koster, Jessica L. Tracy

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
FundersStanford University
KeywordsPsychologyPolitical science

Abstract

fetched live from OpenAlex

Emerging evidence suggests that gender is a defining feature of personhood. Studies show that gender is the primary social category individuals use to perceive humanness and the social category most strongly related to seeing someone—or something—as human. However, the universality of gender’s primacy in social perception and its precedence over other social categories like race and age have been debated. We examined the primacy of gender perception in the Mayangna community of Nicaragua, a population with minimal exposure to Western influences, to test whether the primacy of gender categorization in humanization is more likely to be a culturally specific construct or a cross-cultural and potentially universal phenomenon. Consistent with findings from North American populations [A. E. Martin, M. F. Mason, J. Pers. Soc. Psychol. 123, 292–315 (2022)], the Mayangna ascribed gender to nonhuman objects more strongly than any other social category—including age, race, sexual orientation, disability, and religion—and gender was the only social category that uniquely predicted perceived humanness (i.e., the extent to which a nonhuman entity was seen as “human”). This pattern persisted even in the most isolated subgroup of the sample, who had no exposure to Western culture or media. The present results thus suggest that gender’s primacy in social cognition is a widely generalizable, and potentially universal, phenomenon.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.119
GPT teacher head0.403
Teacher spread0.284 · 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.

Study designTheoretical or conceptual
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

Citations7
Published2024
Admission routes1
Has abstractyes

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