Fair-chance hiring policies aim to expand employment opportunities for individuals with criminal records by reducing legal and systemic barriers to work. These policies include Ban-the-Box, occupational licensing reforms, record-sealing, certificates of rehabilitation, and liability protections. Despite growing adoption, their impact remains difficult to quantify due to limited data. These policies vary between states, creating an uneven and nuanced hiring landscape.
To measure the effect of policies on fair-chance hiring, we (1) introduce standardized metrics to assess the presence and strength of supportive policies, and the extent of legal barriers across all 50 states; and (2) measure employer engagement in fair-chance hiring by analyzing job postings. These metrics enable state-level comparisons, providing data-driven tools to advance the study of fair-chance employment!
You can learn more our peer-reviewed research article for more details.
Meet our Research Team!
Zofia Stanley (she/her) is an applied mathematician and data scientist. She received her BS in mathematics from Brown University and her PhD in applied mathematics from the University of Colorado, Boulder. She did her postdoctoral research at the National Oceanographic and Atmospheric Administration’s Physical Sciences Laboratory. Zofia’s research on seawater density has been incorporated into operational climate models. She also co-founded a course on Race and Gender in the Scientific Community, which is now a permanent course offering at Brown University.
Alayna Johnson (she/her) is a rising senior at Macalester College. She is pursuing a degree in Statistics with a minor in Mathematics and a concentration in Public Health. Alayna enjoys working on health and social justice-related projects in and outside of academia. She is excited to work with QSIDE Institute over the summer and gain valuable experience.
Jocelyn Bliven (they/them) is a rising senior at Williams College studying Computer Science and Women, Gender, and Sexuality Studies. They have done research in cache-optimized algorithms and will be pursuing a senior thesis on how social media algorithms affect sexual identity development. They are interested in studying interdisciplinary problems requiring technical knowledge and a social justice perspective. They are excited to join the QSIDE team!