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Record W2621301104 · doi:10.1002/dev.21527

Scanning of own‐ versus other‐race faces in infants from racially diverse or homogenous communities

2017· article· en· W2621301104 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.

Bibliographic record

VenueDevelopmental Psychobiology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
FundersDivision of Behavioral and Cognitive Sciences
KeywordsRace (biology)Fixation (population genetics)PsychologyHomogeneousFace (sociological concept)DemographyDevelopmental psychologyGerontologyAudiologyMedicineSociologyGender studiesPopulationMathematics

Abstract

fetched live from OpenAlex

We examined the role of community face experience on 6- and 8-month-old Caucasian infants' scanning of own- and other-race face scanning. We measured infants' proportional fixation time and scan path amplitudes as indices of face processing. Proportional fixation time to informationally rich face regions varied as a function of age and face race for infants living in a racially homogeneous community, whereas scan path amplitudes varied as a function of age and face race for infants living in a racially diverse community. In both communities 6-month-old infants did not show different responding to own- and other-race faces, whereas 8-month-old infants responded differently to own- and other-race faces. However, 8-month-old infants from the two communities showed different patterns of cross-race face scanning. Therefore, experience in the community beyond the home appears to contribute to the development of differential scanning of own- versus other-race faces between 6 and 8 months of age.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.200
GPT teacher head0.376
Teacher spread0.176 · 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