From inclusion to inclusivity: A scoping review of community music scholarship
Bibliographic record
Abstract
This article investigates how community music scholarship has taken up inclusion. Using a modified scoping review methodology, the authors analysed 47 articles published in the International Journal of Community Music from 2008 to 2018, examining how scholars have defined and operationalized the terms ‘inclusion’ and ‘inclusivity’, which were used interchangeably in the literature. The authors found that inclusion was often normatively invoked with no definition or approaches provided. In those articles that provided more detail about inclusion, many focused on musical access, such as removing auditions and not requiring previous music skill or knowledge, and processes of musical inclusion, such as creating a friendly and non-judgmental atmosphere, providing multiple ways of engaging with music-making and cultivating musical leadership among participants. Less frequent in the literature were ideas and approaches focusing on social inclusion through music, including frameworks that aimed to address and change systems that create marginalization; approaches that addressed social barriers to participation, such as transportation and childcare; and approaches that decentralized leadership to create collective responsibility and participation. The authors conclude by examining approaches from other scholarly disciplines, arguing that community music scholarship may benefit for more sustained and deliberate use of the term inclusivity, which points to the ongoing practice and effort towards inclusion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.141 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.029 | 0.031 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".