Yaluma, C. B. (2025). The Impact of Statewide Virtual Charter Schools on District Segregation.

Abstract: The increase in the provision of K-12 online "virtual" schooling options has the potential to influence enrollment patterns in brick-and-mortar public schools. Yet, research has largely ignored the impact of online schooling options on segregation within school districts. This study examines segregation patterns in Ohio school districts following the introduction of statewide virtual charter schools and the closure of a large statewide virtual charter school. To investigate, I exploit variation in the proportion of district students enrolling in virtual charter schools across Ohio. This study uses a matched difference-in-differences approach.

Yaluma, C. B., Mallipeddi, R., Hirsch, D. D., & Chandrasekaran, A. (2026). The Impact of Responsible AI Management (RAIM) on Organizational and Market Performance.

Abstract: Artificial intelligence (AI) has become ubiquitous across business functions—from marketing to service operations, to product design and strategic decision-making. As adoption of AI accelerates, concerns over algorithmic error, opacity in model decision-making, and data privacy have become increasingly relevant. As a result, organizations are increasingly expected not only to innovate with AI but also to govern it responsibly. Despite the heightened attention to “Responsible AI,” academic research provides limited insight into two critical questions: (1) how external stakeholders, particularly financial markets, interpret and respond to these RAIM efforts, and (2) whether or not RAIM leads to long-term improvements in operational efficiency and profitability. Our study aims to fill the gap by answering these two critical questions.

Yaluma, C. B., & Hirsch, D. D. (2026). The Governance of Generative AI in the Public Sector: Gen AI Management (GAIM) in K-12 Education.

Abstract: The rapid advancement of Gen AI presents both unprecedented opportunities and challenges across various sectors. In the education sector, Gen AI can bring about benefits such as personalized learning, lesson planning, enhanced teacher evaluations, and increased staff and teacher productivity. However, the use of Gen AI tools also comes with potential risks, including the spread of misinformation, privacy concerns, misapplication, and perpetuation of discrimination, among others. To fully realize the potential of Gen AI, we must maximize the benefits while mitigating the associated risks. In this study, we examine 1) the extent to which school districts are adopting and deploying generative AI at both the district and school levels, 2) the extent to which local school districts develop and implement policies, practices, and processes to govern the use of generative AI among administrative staff, teachers, and students, and 3) use quantitative and descriptive analysis to examine how the use and governance of generative AI differ across schools and districts with varying socioeconomic status. To guide our investigation, we will draw on the bounded rationality model to develop hypotheses about how school districts make governance decisions.

Lavertu, S., & Yaluma, C. B. (2025). The Impact of Collective Bargaining on the Management and Characteristics of District Personnel.

Abstract: Public-sector unions have a direct impact on the management of public agencies and the cost and quality of public-sector personnel. Yet, public administration research has largely ignored the impact of unions on management and staffing. Using unusually rich historical data on the staffing of Ohio school districts, this study examines the impact of introducing union collective-bargaining rights on the management and qualities of school district personnel. Specifically, using an event-study framework, we leverage differences in the timing of districts’ adoption of collective bargaining to estimate its impact on teacher experience, credentials, and demographic characteristics known to affect educational outcomes of diverse students. Our findings indicate that public-sector collective bargaining shifted expenditures toward core instructional functions, increased teacher salaries, and increased the proportion of women in secondary education. We find no effects on teacher qualifications, experience, or racial diversity, and find null (and sometimes negative) effects on student graduation rates. Taken in conjunction with the larger literature on collective bargaining, these results suggest that public-sector unions may contribute to some inefficiencies in government, but that they may also have some positive social benefits by increasing the presence of women in the public workforce.

Hirsch, D. D., Ott, J., Westover-Muñoz, A. & Yaluma, C. B. (2025). Aligning Algorithmic Risk Assessments with Criminal Justice Values. (Pending publication in Federal Sentencing Reporter journal).

Abstract: Federal and state criminal justice systems use algorithmic risk assessment tools extensively. Much of the existing scholarship on this topic engages in normative and technical analyses of these tools, or seeks to identify best practices for tool design and use. Far less work has been done on how courts and other criminal justice actors perceive and utilize these tools on the ground. This is an important gap. Judges’ and other criminal justice actors’ attitudes towards, and implementation of, algorithmic risk assessment tools profoundly affect how these tools impact defendants, incarceration rates, and the broader criminal justice system. Those who would understand, and potentially seek to improve, the courts’ use of these tools would benefit from more information on how judges actually think about and employ them. This article begins to fill in this picture. The authors surveyed Ohio Courts of Common Pleas judges and staff, and interviewed judges and other key stakeholders, to learn how they view and use algorithmic risk assessment tools. The article describes how Ohio Common Pleas Courts implement algorithmic risk assessment tools and how judges view and utilize the tools and the risk scores they generate. It then compares Ohio practice in this area to the best practices identified in the literature and, on this basis, recommends how the Ohio Courts of Common Pleas—and, by implication, other state and federal court systems—can better align their use of algorithmic risk assessment tools with core criminal justice values.

Yaluma, C. B., Little, A. P., & Leonard, M. B. (2021). Estimating the Impact of Expulsions, Suspensions, and Arrests on Average School Proficiency Rates in Ohio using Fixed Effects. Educational Policy, 36(7), 1731-1758.

Abstract: Student removal became an increasingly utilized form of discipline since the implementation of zero-tolerance policies during the early 1990s. Evaluative studies have consistently found negative relationships between student removal and academic success. Majority of cases regarding student removal are for minor and non-violent offenses and literature in this field suggests that teachers’ biases and cultural misreadings widen racial disparities in school discipline and academic performance. Our study estimates the effects of suspensions, school-related arrests, and expulsions under zero-tolerance by exploiting within-school variation in school mean proficiency rates of Asian, Hispanic, Black, and White racial subgroups over a 3-year period. Our findings reaffirm consistent evidence that exclusionary policies have negative effects on academic outcomes. We also find evidence of differential effects by racial subgroup. The paper concludes with a discussion and policy implications.

Yaluma, C. B., & Tyner, A. (2021). Are US Schools Closing the “Gifted Gap”? Analyzing Elementary and Middle Schools’ Gifted Participation and Representation Trends (2012–2016). Journal of Advanced Academics, 32(1), 28-53.

Abstract: This article tests hypotheses by examining variations in the percentage of elementary and middle schools offering gifted and talented programs as well as gifted student participation and representation between 2012 and 2016. Using the Office of Civil Rights and the National Center for Educational Statistics (NCES) Common Core data, we find that between 2012 and 2016, the percentage of schools with gifted programs declined slightly. Crucially, gifted participation is increasing faster in low-poverty schools than in high-poverty schools. Furthermore, suburban schools became more likely to have gifted programs than urban, rural, or town schools. However, gifted participation by urbanicity decreased across all four locales. Using only 2016 data, we show that students who are Black and Hispanic continue to be statistically underrepresented. We conclude with a brief discussion and policy implications.

Yaluma, C. B., & Tyner, A. (2018). Is There a Gifted Gap? Gifted Education in High-Poverty Schools. Thomas B. Fordham Institute.

Abstract: In 2018, the United States continues to see wide and worrying achievement gaps among student groups, despite decades of programs and policies meant to narrow them. Many factors inside and outside the education system contribute to these gaps, but researchers have consistently shown that black, Hispanic, and low-income students tend to enter school far behind their peers, and are then less likely to have access to quality education programming. A related issue is the wide variation in the achievement level of students in any given classroom, school, or grade. A recent study found a range of more than eleven grade levels among fourth graders in a small group of diverse elementary schools. Without differentiated programs for these different students, those who lag behind will miss out on the attention they need to catch up while students who are ahead will become bored and disengaged. Gifted-and-talented programs are a key source of enriched and accelerated academic opportunities for this latter group: the students who are performing--or could perform--well beyond their peers. When high-achieving poor and minority students have less access to these special programs than do their peers, gifted education may exacerbate existing inequalities. To better understand the state of gifted education in the United States today and investigate the extent to which access and participation in gifted programs vary for different students, this report uses federal data to answer three key questions: (1) To what extent do high-poverty schools offer gifted-and-talented programs? (2) What proportion of students in such schools participates in those programs? and (3) How does student participation in those programs vary by race within schools, particularly high-poverty schools? The authors analyze the representation and participation of gifted students using school-level data at the state and national levels. After briefly describing the approach, the authors examine the extent to which schools report offering any gifted programming, analyzing schools by their poverty level and racial and ethnic composition. Next, they turn to student participation and representation, again with an eye toward the school's poverty level as well as student race and ethnicity. Although the emphasis is on high-poverty schools, the authors show national results at all poverty levels and break down the availability and participation in gifted programming by state. These comparisons show the prevalence of such programs in high-poverty schools and the extent of black and Hispanic participation in them. Finally, the authors describe gifted programming in detail for each state via a series of customized profiles.

Saultz, A., Mensa, Q., Yaluma, C. B., & Hodges, J. (2018). Charter School Deserts—High-Poverty Neighborhoods with Limited Educational Options. Thomas B. Fordham Institute.

Abstract: A primary purpose of charter schooling is to provide education options and alternatives for families that are neither satisfied with nor well served by their current schooling options. For that reason, many of today's charter schools are focused on improving educational opportunities for low-income and minority students. Their families seek high-quality school options, yet many lack the means to move out of neighborhoods with unsatisfactory schools or to transport their children to attend schools that are better, but farther from home. School choice policies seek to address this problem in several ways, such as by creating public charter schools. Yet such schools are not evenly distributed across the communities that would benefit from them. For a host of reasons, it's difficult--or impossible--to establish charter schools in many places. There are political, legal, and fiscal obstacles, such as low per-pupil funding for charter students, no access to (or financial help with) suitable facilities, and laws or regulations that confine charters to certain communities or neighborhoods. Yet for a school to serve the children who need and would welcome it--particularly children from poor families--that school must be close to home. This is particularly true of elementary schools, as parents are understandably hesitant to send young children long distances to attend school. This report examines patterns of charter school locations, seeking to answer one fundamental question: "What high-need areas lack charter schools?" The authors analyze the distribution of chartered elementary schools across the country to provide educators and policymakers with information about which needy communities have no ready access to charter schools.

Saultz, A., & Yaluma, C. B. (2017). Equal Access? Analyzing Charter Location Relative to Demographics in Ohio. Journal of School Choice. 11(3), 458–476

Abstract: We analyze the geographical distribution of, and access to, charter schools in the state of Ohio. Using poverty and race data from the U.S. Census, as well as publicly available student achievement scores, we analyze the locational preferences of charter schools. We use Geographic Information System (GIS) to visual display charter school locations relative to these community variables. Results suggest that policies limiting charters to locate in low performing school districts (labeled “challenged districts”) lead charters to cluster in urban cities; thus students living in poverty in large portions of the state lack easy access to school choice options. Further, we find that charters tend to avoid areas of the highest concentrations of poverty and Hispanic (though not Black) students.