Exploring Songwriting as an Expression of Grief on Cape Breton Island: A Qualitative Interview Study
Bibliographic record
Abstract
Located in Nova Scotia, Canada, Cape Breton Island has a rich and diverse musical history, which includes a well known tradition of using songwriting as a mourning practice. In the cultural mosaic of Canada, individuals seeking music therapy bring unique and diverse cultural backgrounds and experiences. Exploring these inherent cultural practices can offer models for integrating songwriting into the bereavement music therapy session while also informing music therapy training programs and future research. Grounded in a social constructivist epistemology (Hillier, 2016) and using qualitative semi-structured interviews, this study explored the use of songwriting as an expression of grief for three Cape Breton Island songwriters. Utilizing inductive thematic analysis (Braun & Clarke, 2006), three themes emerged from the data. The first theme, transformative grief journey, reflects how participants experienced personal growth while moving through a unique journey through their grief. Songwriting helped them process a range of emotional responses, provided a safe outlet for difficult feelings, and supported their ability to move forward. The second theme, cultivating connection, highlights how songwriting reduced feelings of isolation and helped participants feel connected to others through sharing their music. The third theme, intrinsic practice, describes how participants trusted the songwriting process and emphasized its cultural importance as an inherent and meaningful way to express grief.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".