Facilitating Access to Healthcare for Performing Artists Using Subsidized Health Services in Canada: An Interpretive Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Performing artists are often confronted with job insecurity and insufficient health coverage. As a result, artists may not have access to non-publicly funded health services that are essential to their well-being. A health centre in Canada that specializes in providing healthcare to artists offers eligible artists subsidized health services, with the aim to treat acute health issues that impact an artists' ability to engage in their artistic practice. PURPOSE: We evaluated the use of the subsidized health services and explored the subsidy recipients' and the selection committee's perspectives on the impact of these services on the health of performing artists. METHODS: We applied an interpretive descriptive approach to our qualitative inquiry. We conducted individual, semi-structured interviews with recipients of the subsidy and a focus group with the selection committee that selected recipients of the subsidy. Data were analyzed using thematic analysis. RESULTS: A total of 14 artists and all members of the selection committee (n=3) participated. Recipients and selection committee perceived that subsidized health services were critical in enabling consistent and timely diagnosis and treatment. Several themes emerged from the data: 1) need for universal health benefits to restore equity and offset healthcare insecurity, 2) the critical role of subsidies in accessing health services, 3) risks of abruptly ending health services when subsidy runs out, 4) barriers in applying for and accessing subsidies, 5) mental health challenges, and 6) importance of the subsidy in the context of the COVID-19 pandemic. All recipients saw noticeable improvement in health outcomes that they believed would have been otherwise unattainable if they did not have timely access to care. CONCLUSIONS: Subsidized health services play an important role in ensuring that performing artists have access to care for injuries and health conditions that are related to their profession. Future research can examine the long-term impact of subsidized services on the recipients' health and employment outcomes.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".