Bibliographic record
Abstract
This Special Issue of the International Journal of Community Music ( IJCM ), ‘Practitioner Perspectives’, places the spotlight on writing by and about practitioners. The lead article, by Kathleen Turner, Alexis Anja Kallio, Helen Phelan and Naomi Sunderland, thoughtfully engages in a knowledge mobilization exercise based on a series of online conversations between practitioners and researchers in Ireland and Australia. Staying with the Australian context, Brydie-Leigh Bartleet, Mat Klotz, Pearly Black, Joel Spence, Chi Lui Flora Wong and Emma Heard engage in a playful but rigorous exercise of using the Möbius strip as an analytic device to illustrate and understand the interplay between community music and social impact. In the third article, Nerissa Rebagay and Ryan Rebagay use the lens of community music therapy to examine the Miami Jam Sessions, a programme for neurodivergent people to build meaningful relationships and foster social connections through music. The next four articles focus on Canadian contexts. Mason Micevski, creative director of Emerson Arts in Hamilton, Ontario, thoughtfully explores assumptions around musical theatre as a safe space for 2sLGBTQIA+ individuals. In the tradition of cultural mapping, Thomas Barker’s article ‘maps’ the city of Edmonton’s system of ‘community leagues’. The final two articles, one by Louise Campbell and Deanna Yerichuk, the other by Roger Mantie, discuss online databases: the Participatory Creative Music Hub and the Canadian Community Music Group Database, respectively. The former details the activity of those who lead participatory music making, the latter provides a resource of over 1600 groups for those who engage in intact participatory music groups.
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 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 | 0.019 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.035 | 0.028 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".