American public universities have assumed business-minded practices and norms that more closely align with the goals and values of corporations than social institutions charged with creating and disseminating knowledge. One consistent strategy to lower costs involves faculty labor. Institutions have outsourced educational missions to a largely contingent workforce to decrease instructional costs; over the last two decades, the number of adjunct or part-time faculty now comprises 70% of all faculty. As a result, policies have decreased instructional costs and provided administrators with increased flexibility to respond to student demands. However, research indicates compromised student outcomes, less shared governance, and faculty work–life pressures that can undermine commitment, motivation, and professional identity. The following literature review examines the locus of academic capitalism and faculty labor, theorizing how faculty labor policies infer consequences for equity, inclusion, and social justice in higher education.

This mixed-methods study examines the impact and implementation of Nevada’s weighted student funding (WSF) model that targets funding to students with the greatest need. We use event study models to analyze student achievement data from 2017–2018 to 2021–2022 and qualitative in-depth interviews with school district and school administrators to explore perceptions of the new funding model. Our quantitative findings suggest that Nevada’s WSF helped improve student achievement overall, but it did not mitigate achievement disparities between targeted and non-targeted students. Our qualitative data reveal administrators’ implementation concerns, especially in designing programming to support students intending to benefit from the additional funds. Our findings highlight the tension between WSF’s two distinguishing features—targeted funding based on student needs and school administrator autonomy.

This multistage mixed methods study investigated the outcomes of a state’s new K-12 weighted student funding formula, which aimed to better support students with additional needs: English Learners and students experiencing poverty. Intentional data integration throughout the study produced new areas for hypothesis testing and data analysis. Our initial quantitative strand deductively relied on education production function models to determine the efficacy of the weighted funding formula. Qualitative analyses explored the consequences of the funding model from the perspectives of school and district administrators, identifying an extreme case among rural participants. Further quantitative analyses compared outcomes in urban and rural schools. Using a mixed methods approach, we uncovered unforeseen policy priorities for the state and enhanced a study of education production.