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Record W2132301564 · doi:10.1348/174866407x231029

Infant preference for female faces occurs for same‐ but not other‐race faces

2008· article· en· W2132301564 on OpenAlexaff
Paul C. Quinn, Lesley Uttley, Kang Lee, Alan Gibson, Michael Smith, Alan Slater, Olivier Pascalis

Bibliographic record

VenueJournal of Neuropsychology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsRace (biology)PreferencePsychologyDevelopmental psychologyFace (sociological concept)Social psychologyGender studies

Abstract

fetched live from OpenAlex

There has been a recent surge of interest in the question of how infants respond to the social attributes of race and gender information in faces. This work has demonstrated that by 3 months of age, infants will respond preferentially to same-race faces and faces depicting the gender of the primary caregiver. In the current study, we investigated emergence of the female face preference for same- versus other-race faces to examine whether the determinants of preference for face gender and race are independent or interactive in young infants. In Expt I, 3-month-old Caucasian infants displayed a preference for female over male faces when the faces were Caucasian, but not when the faces were Asian. In Expt 2, new-born Caucasian infants did not demonstrate a preference for female over male faces for Caucasian faces. The results are discussed in terms of a face prototype that becomes progressively tuned as it is structured by the interaction of the gender and race of faces that are experienced during early development.

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)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.259
GPT teacher head0.376
Teacher spread0.117 · 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

Citations164
Published2008
Admission routes1
Has abstractyes

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