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Record W4411114849 · doi:10.1386/ijcm_00121_2

Editorial: On sustaining and diversifying community music

2025· editorial· en· W4411114849 on OpenAlexaff
Roger Mantie

Bibliographic record

VenueInternational Journal of Community Music · 2025
Typeeditorial
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsCognitive sciencePsychologySociologyCommunicationAestheticsArt

Abstract

fetched live from OpenAlex

Issue 18:1 of the International Journal of Community Music includes articles that address diversity and financial sustainability in community music activity. Research by MacGregor and Pitts examines the problem of declining membership in recreational choirs in the United Kingdom and how this may reveal unfavourable attitudes and commitments to diversity and inclusion. The study by Crooke and associates draws attention to disparities in funding and support for practitioners and participants from racialized groups in Australia participating in an intercultural music programme. Allison and associates examine ‘facilitators and barriers to sustainment’ of community choir programming in the United States. Among their recommendations are to explore organizations outside of traditional government arts funders, such as ageing services organizations. Cassman’s study of the Fresh Tracks programme for ‘justice-involved young adults’ in California demonstrates that even when programming is sufficiently funded, participation levels may be low if structural conditions such as location and transportation are not sufficiently addressed. The large-scale study by Castro-Cifuentes and associates demonstrates that, while other motivators may also be at play, musical motivations provide a strong sense of purpose and identity for community music practitioners.

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)0.008
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.024
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.030
Meta-epidemiology (narrow)0.0060.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.003
Science and technology studies0.0060.004
Scholarly communication0.0110.008
Open science0.0060.003
Research integrity0.0240.022
Insufficient payload (model declined to judge)0.0200.016

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 head0.120
GPT teacher head0.302
Teacher spread0.181 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2025
Admission routes1
Has abstractyes

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