MétaCan
Menu
Back to cohort
Record W3026833136 · doi:10.1163/25902539-00202008

“Can We Have More Hand-Drums?” Preschool Children's Musical Play in a Program Exploring Diverse Languages

2020· article· en· W3026833136 on OpenAlexaff
Aleksandra Acker

Bibliographic record

VenueBeijing international review of education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsMusicalPsychologyVariety (cybernetics)PedagogyPeriod (music)Cultural learningMusic educationVisual artsAestheticsArtComputer science

Abstract

fetched live from OpenAlex

This paper explores the role of play in a research project that documented and elucidated responses to a culturally diverse music program of five preschool-aged children in a child-care centre in Melbourne, Australia. The study was conducted over a period of nine weeks. The music program was conducted playfully, concentrating not only on the musical features and premeditated pedagogical devices, but on children's contribution to the content and arrangements of the music sessions. The methodology employed in the study was conceptually rooted in the socio-cultural framework. The researcher took into consideration that learning is purported in a social environment and changes in character within a variety of social contexts. The social aspects of play were well-captured in the large number of Learning Stories that were written about and with the children. The Learning Story method of gathering, analysing and planning from data was employed as this socio-cultural approach encompassed contextual factors and celebrated children's active role in the process of learning within and beyond the music program. The analysis of Learning Stories revealed that children's learning is more profound when there are opportunities for play, on their own terms; this consideration is strongly recommended for future research projects.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.998

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 head0.080
GPT teacher head0.327
Teacher spread0.247 · 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 designNot applicable
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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBeijing international review of educationSame topicDiverse Music Education InsightsFrench-language works237,207