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Race, Ethnicity, and Culture in Child Development: Contemporary Research and Future Directions

2006· editorial· en· W2145351176 on OpenAlexaff
Stephen M. Quintana, Frances E. Aboud, Ruth K. Chao, Josefina M. Contreras‐Grau, William E. Cross, Cynthia Hudley, Diane Hughes, Lynn S. Liben, Sharon Nelson‐Le Gall, Deborah L. Vietze

Bibliographic record

VenueChild Development · 2006
Typeeditorial
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsEthnic groupRace (biology)PsychologySociocultural evolutionImmigrationChild developmentContext (archaeology)Identity (music)Developmental psychologySocial psychologySociologyGender studiesPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

The editors of this special issue reflect on the current status and future directions of research on race, ethnicity, and culture in child development. Research in the special issue disentangles race, ethnicity, culture, and immigrant status, and identifies mediators of sociocultural variables on developmental outcomes. The special issue includes important research on normal development in context for ethnic and racial minority children, addresses racial and ethnic identity development, and considers intergroup processes. The methodological innovations as well as challenges of current research are highlighted. It is recommended that future research adhere to principles of cultural validity described in the text.

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)0.011
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0030.003
Science and technology studies0.0040.004
Scholarly communication0.0090.007
Open science0.0030.002
Research integrity0.0100.020
Insufficient payload (model declined to judge)0.0050.002

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 head0.030
GPT teacher head0.345
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations290
Published2006
Admission routes1
Has abstractyes

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