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Face Processing in Infancy and Beyond: The Case of Social Categories

2019· review· en· W2907124753 on OpenAlexaff
Paul C. Quinn, Kang Lee, Olivier Pascalis

Bibliographic record

VenueAnnual Review of Psychology · 2019
Typereview
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyDevelopmental psychologyPerceptionRace (biology)Face (sociological concept)Face perceptionCognitive psychology

Abstract

fetched live from OpenAlex

Prior reviews of infant face processing have emphasized how infants respond to faces in general. This review highlights how infants come to respond differentially to social categories of faces based on differential experience, with a focus on race and gender. We examine six different behaviors: preference, recognition, scanning, category formation, association with emotion, and selective learning. Although some aspects of infant responding to face race and gender may be accounted for by traditional models of perceptual development, other aspects suggest the need for a broader model that links perceptual development with social and emotional development. We also consider how responding to face race and gender in infancy may presage responding to these categories beyond infancy and discuss how social biases favoring own-race and female faces are formed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.100
GPT teacher head0.460
Teacher spread0.361 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations86
Published2019
Admission routes1
Has abstractyes

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