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Record W3028292739 · doi:10.1163/25902539-00202007

Developing Children's Cultural Identities through Play

2020· article· en· W3028292739 on OpenAlexaff
Winnie Sin Wai Pui, Heyi Zhang, Ding Ming, ZHONG Cai E

Bibliographic record

VenueBeijing international review of education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsMindsetCurriculumCultural competencePedagogyPsychologyCompetence (human resources)LiteracyEarly childhoodQualitative researchEarly childhood educationCultural diversityChinaMathematics educationDevelopmental psychologySociologySocial psychologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Play is an important vehicle for developing literacy, cognition, and social competence in early years settings. In this paper, a qualitative case study in a private kindergarten in China indicated how children could learn and appreciate their own culture in a thoughtfully designed play-based setting. Thirty kindergarten teachers from 15 classes consisting of 431 children in total participated in this study. Based on field notes, audio and video recordings, and teachers’ self-reflective notes, the study explored the play-based setting within a curriculum framework, i.e. the Early-years Whole-person Global-mindset Curriculum Framework (ewgc). The results showed that the play-based setting supported young children to form their own cultural identities and enhanced children's development in general.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.001
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 head0.051
GPT teacher head0.400
Teacher spread0.349 · 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 designQualitative
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

Citations4
Published2020
Admission routes1
Has abstractyes

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