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Record W2763389436 · doi:10.1111/cdev.12971

A Long-Term Effect of Perceptual Individuation Training on Reducing Implicit Racial Bias in Preschool Children

2017· article· en· W2763389436 on OpenAlex
Miao Qian, Paul C. Quinn, Gail D. Heyman, Olivier Pascalis, Genyue Fu, Kang Lee

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChild Development · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPsychologyDevelopmental psychologyIndividuationPerceptionTerm (time)Cognitive psychologyPsychotherapist

Abstract

fetched live from OpenAlex

= 5.64 years) implicit pro-Asian/anti-Black racial bias. Initial training to individuate other-race Black faces, followed by supplementary training occurring 1 week later, resulted in a long-term reduction of pro-Asian/anti-Black bias (70 days). In contrast, training Chinese children to recognize White or Asian faces had no effect on pro-Asian/anti-Black bias. Theoretically, the finding that individuation training can have a long-term effect on reducing implicit racial bias in preschoolers suggests that a developmentally early causal linkage between perceptual and social processing of faces is not a transitory phenomenon. Practically, the data point to an effective intervention method for reducing implicit racism in young children.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.367
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.061
GPT teacher head0.367
Teacher spread0.306 · 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