Use of Subsidized Health Services by Artists in Canada: An Exploratory Study
Bibliographic record
Abstract
IntroductionCreative and performing artists are often confronted with precarious employment and insufficient healthcare coverage. A clinic in Canada that provides specialized healthcare to artists offers eligible artists subsidized health services. We aim to compare the use of health services, demographics and health conditions between subsidy artist recipients (SAs) and non-subsidy artists (NSAs).MethodsWe accessed existing data from 265 SAs and 711 NSAs and applied descriptive and inferential statistics to address our research questions.ResultsMusculoskeletal issues, stress, anxiety disorders, and depressive disorders are the most common health problems faced by SAs. Compared to NSAs, SAs were more likely to seek treatment for stress, but less likely to seek treatment for anxiety disorders, depressive disorders, chronic problems, and upper extremity problems.DiscussionFuture research may investigate the enduring effects of subsidized health services on SAs' health outcomes. Sustained positive outcomes are crucial for maintaining an artist's career and well-being.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".