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Record W7144698739

子どもの歌の伝承に関する考察 ―ソーシャルメディア普及による環境変化の現状と課題―

2025· article· ja· W7144698739 on OpenAlexaff
範之 鈴木

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2025
Typearticle
Languageja
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsFocus (optics)Key (lock)Core (optical fiber)Front (military)
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the transmission of children's songs, exploring how Warabeuta (traditional Japanese children's songs), Shoka (school songs), and Doyo (modern children's songs) have been passed down through different eras. It also identifies challenges presented by today's environment, significantly altered by the widespread adoption of social media. The core essence of Warabeuta, as described by Koizumi, and the Doyo theories of Hakushu and Ujo, seem to serve as timely warnings, even across generations, against the potential alteration of children's songs due to social media's pervasive influence. When considering whether children's songs and hand-play songs should be viewed primarily as "play" or as "works," institutions training early childhood educators should present both viewpoints. However, the ultimate focus should be on fostering enjoyment with the children directly in front of us. It's crucial to build relationships where joy is co-created with children through "songs" and "words," all while respecting the original creators. Establishing clear guiding principles and effective methods for this approach will be a key objective for future research.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.033
GPT teacher head0.269
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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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