Who counts as an artist—and who gets left out? Our new study compares federal labor data with applicants to a major guaranteed income program for artists. The findings reveal major gaps in how artists are defined and show how inclusive policies can better reach the full spectrum of creative workers.
Introduction: Why Definitions Matter
In a recently published article in Cultural Trends, we investigate how artists are defined in both cultural policy and labor statistics, and why those definitions matter. Drawing on data from Creatives Rebuild New York’s (CRNY) Guaranteed Income for Artists (GIA) program, we compare two different pictures of the artistic workforce: one based on self-identification and inclusive eligibility criteria, and another derived from standard federal labor market classifications. Our analysis shows that relying solely on official data sources misses significant portions of the artist population—especially those from marginalized backgrounds or less commercialized disciplines.
Two Datasets, Two Definitions of “Artist”
CRNY’s GIA program provided 2,378 artists across New York State with unconditional monthly payments of $1,000 for 18 months. More than 21,000 individuals applied, all of whom identified as artists, culture bearers, or culture makers. The program defined eligibility broadly—no formal credentials, income minimums, or artistic quality assessments were required. Instead, applicants needed to demonstrate a sustained engagement with artistic practice and fall below a self-sufficiency income threshold.
To understand how this pool of self-identified artists compares to official statistics, we analyzed data from the 2022 Current Population Survey (CPS), which uses the U.S. Census Bureau’s Standard Occupational Classification (SOC) system. The CPS captures only those whose primary job aligns with recognized artistic occupations, such as designers, musicians, and writers. It does not include those who work part-time in the arts, combine artistic and non-artistic jobs, or operate outside conventional employment arrangements.
What Federal Surveys Miss
The demographic and occupational differences between the two datasets are striking. Artists in the CPS are more likely to be white, male, and employed in commercially oriented sectors like design and publishing. By contrast, GIA applicants were far more diverse. Over half identified as LGBTQ+, nearly a quarter as multi-gender, and a large share were people of color, immigrants, disabled individuals, caregivers, or formerly justice-involved. These characteristics—often unmeasured or poorly captured in federal surveys—illustrate the limitations of conventional data tools in representing the full range of creative workers.
The GIA applicant pool also included artists working in disciplines that are underrepresented in the CPS. These included craft, performance, oral traditions, interdisciplinary work, and social practice—fields that may not map neatly onto SOC codes or generate consistent wage income. In effect, the CPS tends to reflect artists who have stable jobs and stronger ties to commercial markets, while the GIA data surfaces artists embedded in community work, informal economies, or culturally specific practices.
Testing Definitions: Who Qualifies as an Artist?
To assess whether GIA applicants would meet more conventional definitions of an artist, we examined responses from a follow-up survey. We benchmarked them against widely used criteria in the literature: time spent on artistic work, income derived from art, public or peer recognition, and self-identification.
The results were clear. Over 97% of GIA applicants reported engaging in artistic activity within the past year, and nearly 90% had earned income from it. Most respondents also reported not being dissatisfied with the quality of their own work, and nearly all—97%—self-identified as artists. Even when applying more restrictive definitions, such as engagement in the past month or receipt of formal awards, a majority still qualified.
Interestingly, participants selected for the program (via a weighted lottery that prioritized vulnerability) were slightly more likely to meet these criteria than the overall applicant pool. This suggests that inclusive eligibility standards do not dilute artistic legitimacy; instead, they expand access while still capturing individuals deeply engaged in creative labor.
A Model for Inclusive Policy Design
We further tested the effects of CRNY’s selection process using Monte Carlo simulations based on CPS data. These simulations replicated the program’s weighted lottery and showed that artists who identified as non-white, LGBTQ+, transgender, disabled, or immigrants were selected at higher rates than would occur randomly. However, the actual GIA participants exhibited even more concentrated need than the simulated outcomes, pointing to the program’s effectiveness in reaching vulnerable artists—many of whom fall through the cracks of both arts funding and the broader welfare system.
Notably, over 70% of GIA participants reported receiving no other form of public assistance, despite qualifying under the Self-Sufficiency Standard. This highlights a significant gap in existing safety nets and suggests that artist-targeted guaranteed income can serve as an important complement to more general poverty alleviation programs.
Policy Implications
These findings have several implications for the design of cultural labor policy and data infrastructure:
- First, definitions of “artist” should move beyond narrow occupational codes and account for the diversity of work arrangements, disciplines, and identities in the creative sector.
- Second, artist support programs can adopt multidimensional criteria—including self-identification, engagement, and artistic intent—to widen access without compromising legitimacy.
- Third, better data collection tools are needed to capture the full spectrum of artistic labor, especially among artists working in non-commercial or community-based contexts.
By recognizing artistic identity as a flexible and overlapping category—a “fuzzy set,” in social science terms—policy can more effectively reach those who contribute to cultural life but are overlooked by conventional systems.
References
Pearce, D., & Brooks, J. (2000). The Self-Sufficiency Standard for New York. New York: Women’s Center for Education and Career Advancement. Retrieved from https://selfsufficiencystandard.org/new-york/
Creatives Rebuild New York. (2022). Guaranteed Income for Artists Program. Retrieved from https://www.creativesrebuildny.org/guaranteed-income/
U.S. Census Bureau. (2022). Current Population Survey, March 2022 Annual Social and Economic Supplement (ASEC). Retrieved from https://www.census.gov/programs-surveys/cps.html
About the article
Woronkowicz, J., Noonan, D., & Malone, H. C. (2025). Basic income for artists programs: Who are the artists? Cultural Trends. Advance online publication. https://doi.org/10.1080/09548963.2025.2525208
About the authors
Joanna Woronkowicz is an Associate Professor at the O’Neill School of Public and Environmental Affairs at Indiana University and Faculty Director at the Center for Cultural Affairs. Her research focuses on labor, capital, and technological investments in the arts.
Douglas Noonan is a Professor at the O’Neill School at Indiana University–Indianapolis and Faculty Director at the Center for Cultural Affairs. His research focused on urban economics, policy evaluation, and the economics of culture and the creative sector.
Harry Cash Malone recently completed his undergraduate degree at Vassar College studying philosophy. He will begin his M.Phil. at Oxford University in Fall 2025.
About the image
