Community Singing as Troubled Learning: Exploring Musical, Social, and Ethical Dimensions of Safety and Risk among Adult Singers
Bibliographic record
Abstract
How are safety and risk negotiated within community singing? Many group facilitation techniques within adult education take as foundational that participants must feel safe to participate fully in group learning. This concern for participants safety acknowledges that power and privilege circulate unequally within any social learning context, shaped by race, gender, class, ability, sexual orientation, and in the case of singing, musical competencies. However, community singing can be safe without being comfortable. Comfort, therefore, is not the same as safety, although the two concepts are often conflated. A lack of ease with the process and/or content suggests a possibility of risk for learners as they brush up against the edge of what they know. In this paper, I argue that along a continuum of, on the one end feeling both safe and comfortable, and on the other end feeling unsafe (which inherently suggests extreme discomfort), the deepest musical and social learning constantly negotiates a tension between safety and discomfort. Using Joyces analysis (2003) of safety in community singing contexts as my point of departure, I will unpack the concept of safety within musical learning contexts, and how safety is related to, but distinct from, comfort and risk. I will then look specifically at community singing for adults and the particular challenges and possibilities negotiating safety and risk that this context offers. Finally I interrogate whether a balance of safety and risk can truly be achieved for a group of learners who occupy diverse and often oppositional subjectivities. Community singing facilitators grappling with social and cultural considerations of safety and risk create sites of troubled learning for participants, moving beyond the technicism of vocal skills-building towards fostering transformative learning through song.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".