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Sub-Saharan African Musical Learning Communities

2023· book-chapter· en· W4388826585 on OpenAlexaff
Emily Achieng’ Akuno, Akosua O Addo, Elizabeth Andang’o, Andrea Emberly, M Davhula, Perminus Matiure

Bibliographic record

VenueOxford University Press eBooks · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsYork University
Fundersnot available
KeywordsShonaTraditional musicMusicalIndigenousContext (archaeology)Traditional knowledgeMusic educationSociologyMusic GeographyIdentity (music)Scope (computer science)PedagogyMusic historyAestheticsGeographyVisual artsArtLinguisticsComputer science

Abstract

fetched live from OpenAlex

Abstract This chapter tackles the childhood music practiced in traditional and modern African settings with emphasis on teaching and learning as facilitated and enhanced by children’s songs and music-making. The spaces where music making takes place, the types of children’s music material, and the occasions during which children make music today are explored from the context of South Africa’s Venda, Zimbabwe’s Shona, Ghana’s Akan, and Kenya’s Luo communities and cultural practices, as representative people of Sub-Saharan Africa. The music practices are interrogated as elements of the African Indigenous Knowledge System, a complex entity from which communities derive their identity and make sense of their existence. The school plays a role in providing scope, modalities, and context for cultivating children’s growth through the use of music in teaching, teaching music, and employing music in non-class situations for learners’ aesthetic development, cultural, and intellectual growth.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.086
GPT teacher head0.210
Teacher spread0.125 · 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
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

Citations2
Published2023
Admission routes1
Has abstractyes

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