Music museum curatorship: Reclaiming rights and responsibilities for musicking on Minjerribah (North Stradbroke Island), Australia
Bibliographic record
Abstract
The Music Curator describes a staged approach to support the reclamation of rights and responsibilities for music-making on Minjerribah (North Stradbroke Island), in southern Moreton Bay, Queensland. This is part of enabling a localised movement toward claiming agency for planning the future course of musical development—especially early childhood musical development. The stages are to firstly understand the local music history from the perspective of local people. Secondly, the person-environment-occupation transactions are described to understand people’s musical relationships to Country. The Person-Environment-Occupation (P-E-O) Model, developed by Canadian occupational therapists (Mary Law and colleagues, 1996), is commonly used to assist individuals to adapt their occupational performance to adverse circumstances. Finally, local people and stakeholders are invited to engage in a strategic planning process to develop Music Action Plans for facilitating community musical development in the future. These stages of musical development are briefly discussed in this paper to highlight the role of the Music Curator, as an occupational therapist and ethnomusicologist, who facilitates the creative process. There are indications that the P-E-O model can be applied to the new context of music curatorship, especially for cultures with strong environmental relationships.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".