Featurette on a select research project
Understanding Career Pathways and Increasing Diversity: A Retrospective Look at Recently Graduated Licensed Practical Nurses and Registered Nurses by Dr. Yetty Shobo, Deputy Director, Healthcare Workforce Data Center and Data Analytics Division at the Virginia Department of Health Professions. To increase diversity in higher income healthcare professions, it is critical to understand pre-career factors that may determine employment in such professions. The Virginia Longitudinal Data System (VLDS) provides a wealth of data needed to embark on such an investigation by linking K-12, post-secondary, and workforce data. Specifically, this study compares the career pathways of licensed practical nurses (a lower income group) and registered nurses (a higher income group). It found that taking a career technical education course and being identified as economically disadvantaged in K-12 were associated with a lower likelihood of becoming a registered nurse rather than a licensed practical nurse; however, this finding didn’t hold for economically disadvantaged Blacks and Hispanics. Further, those who were in a K-12 gifted program or who attended a public rather than a private college were more likely to end up as RNs rather than LPNs. This study will explore these findings further and more information is available at http://www.dhp.virginia.gov/PublicResources/HealthcareWorkforceDataCenter/
Ghosts in the Machine: An Ongoing Series of Equity in Data Analysis by Scott Murrah, Data Analyst, Virginia Community College System
Part 1: Let’s Stop Pretending Data Are Objective. A common theme in an increasingly data-centric world is the supposed objectivity of numbers. We need to understand that objectivity is a platonic ideal, as our decisions are colored by our own identities, as well as the systems we both work with and within. Our race, gender, class, and other identities affect our opinions on policing and the assumptions we make about the topic.1 When it comes to measuring race, there has been an increasing shift in the view of Hispanic/Latino people viewing that identity as their race2 and yet the US Census does not capture it as such3, instead forcing respondents to choose a different identity. With housing segregation being worse now than before Brown vs Board of Education4, adding zip code to models will skew outcomes towards race and class-based biases5. We simply cannot be objective in a subjective world, and neither can the data we work with.
1 Weitzer, R., & Tuch, S. (2006). Race and policing in America. Cambridge University Press.
2 Gonzalez-Barrera, A., & Lopez, M. (2015). Is being Hispanic a matter of race, ethnicity or both?. Pew Research Center. Retrieved 23 March 2022, from https://www.pewresearch.org/fact-tank/2015/06/15/is-being-hispanic-a-matter-of-race-ethnicity-or-both/.
3 US Census Bureau (2022). About the Topic of Race. Census.gov. Retrieved 23 March 2022, from https://www.census.gov/topics/population/race/about.html.
4 Reardon, S., & Owens, A. (2014). 60 Years After Brown: Trends and Consequences of School Segregation. Annual Review Of Sociology, 40(1), 199-218. https://doi.org/10.1146/annurev-soc-071913-043152
5 Zuberi, T., & Bonilla-Silva, E. (2008). White logic, white methods. Rowman & Littlefield
5 Zuberi, T., & Bonilla-Silva, E. (2008). White logic, white methods. Rowman & Littlefield
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