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Development of Executive Functions in Preschoolers with Different Sibling Positions

2023· article· en· W4390780445 on OpenAlexfundno aff
Оlga V. Almazova, Ksenia O. Mostinets

Bibliographic record

VenueRUDN Journal of Psychology and Pedagogics · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
FundersRussian Science FoundationUniversity of Illinois at Urbana-ChampaignUniversity of British ColumbiaUniversity of Cambridge
KeywordsExecutive functionsPsychologySiblingDevelopmental psychologyNeuropsychologyCognitionWorking memory

Abstract

fetched live from OpenAlex

The development of the executive functions in older preschoolers largely determines their subsequent successful adaptation and schooling. The purpose of the research is to identify the developmental features of the executive functions in older preschoolers with different sibling positions. The relevance of the theme is due to the growing number of children with insufficient development of self-regulation. The study involved 393 preschoolers attending senior groups of kindergartens: 153 - single children in the family, 99 - oldest, 21 - middle, 110 - youngest children, 10 - twins). The levels of development of the participants’ executive functions were determined using three subtests of the neuropsychological complex NEPSY II (“Inhibition”, “Sentences Repetition” and “Memory for Design”) as well as the “Dimensional Change Card Sort” technique by F. Zelazo. It was revealed that auditory-speech memory is best developed in the oldest children in the family. The results obtained make it possible to suggest a different structure of connections between different components of executive functions in children with different sibling positions. The level and structure of the developed executive functions in the single and youngest children in the family are more similar to each other than in the oldest and single children or in the oldest and youngest ones.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.467

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)0.0000.000

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 head0.131
GPT teacher head0.444
Teacher spread0.313 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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