Becoming visible: Exploring the meaning of busking for a person with mental illness
Bibliographic record
Abstract
Background: Busking is a long-standing occupation associated with entertaining others in public places for donations, and is enjoyed globally. Yet, little research has been conducted on this occupation or its mental health benefits.Aim: A single case study design was selected to explore the meaning of busking for James, an individual who has a mental illness.Methods: Three in-depth interviews were used to explore the meaning of busking. Data were analyzed inductively and categorized using Spradley’s domain analysis.Results: For James, busking provides a mission in life and a means of visibility, acknowledgement, and contribution to society. Busking also serves a variety of practical purposes, such as making ends meet, and has other unanticipated benefits. While James identified busking as what he was meant to do and providing a means of recovery, he also identified barriers to participation for others considering busking as occupation.Conclusions: For one individual with a mental illness, busking served as occupational means to a variety of outcomes, including improved mental health and well-being. Researchers are encouraged to use single case designs to further understandings of the idiosyncratic nature of participation in occupations and how they promote health.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.010 |
| 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".