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Record W2988557509 · doi:10.1371/journal.pone.0223056

Contextual variation in young children’s acquisition of social-emotional skills

2019· article· en· W2988557509 on OpenAlexfundno aff
Dana Charles McCoy, Jorge Cuartas, Marcus Waldman, Günther Fink

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersGrand Challenges Canada
KeywordsVariation (astronomy)Social emotional learningPsychologyDevelopmental psychologyPhysics

Abstract

fetched live from OpenAlex

This study examined variation in the timing of 5,447 infants' and toddlers' reported acquisition of 12 basic social-emotional skills across and within 11 developing and developed country sites. Although children differed significantly across sites in when they attained social-emotional skills on average (e.g., M age Brazil = 20.50 months vs. M age India = 26.92 months), there was also substantial heterogeneity across skills. For example, children in Pakistan were reported to demonstrate sympathy on average seven months earlier than their peers in Ghana, whereas the opposite was true for sharing. Overall, country-level health and education were strongly associated (r > .60) with earlier site-level skill attainment. In addition to heterogeneity across sites, we also observed notable within-site variability in skill development (ICCs = .03 to .38). Future research is needed to identify sources of variability and how to promote skills that matter within a given context.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
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 science0.0000.000
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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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.

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

Citations22
Published2019
Admission routes1
Has abstractyes

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