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Record W4280500782 · doi:10.1386/eta_00093_3

Drawing as an encounter with materials in early childhood education spaces

2022· article· en· W4280500782 on OpenAlexaff
Kwang Dae Chung

Bibliographic record

VenueInternational Journal of Education through Art · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsCreativitySpace (punctuation)Early childhoodEarly childhood educationPsychologyProvocation testPedagogySociologyVisual artsAestheticsDevelopmental psychologyArtSocial psychologyMedicineLinguistics

Abstract

fetched live from OpenAlex

Some early childhood educators believe that if they provide rich materials for young children, children’s creativity and art will naturally follow and grow. However, materials themselves are not a magical provocation for young children’s artmaking. When young children and educators engage with materials, the materials may become magical and their exchanges may enable a respectful and mindful pedagogical learning space. When educators, children and materials interact with each other, ask questions, listen to each other and share their thoughts and wonderings, the space may transform into collective, collaborative and pedagogical.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.990

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.015
GPT teacher head0.284
Teacher spread0.270 · 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 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
Published2022
Admission routes1
Has abstractyes

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