2.3 Evaluative Frameworks for Disciplinary Risk and Structural Closure
The methodological framework for investigating program closure risk operates through a dual-level analytical design that links macro-level state funding mechanisms to micro-level institutional restructuring decisions. As state authorities increasingly deploy outcomes-based formulas to direct higher education allocations, policy makers conceptualize these metrics as instruments to enhance the transparency of public expenditure and incentivize targeted goals; nevertheless, the systemic consequences remain difficult to control (Performance-Based Funding of Universities in Europe, 2016). To trace how macro-level incentives translate into disciplinary vulnerability, this study operationalizes an evaluative protocol that examines institutional policy documents and restructuring directives. Historically, educational institutions counter budgetary shortfalls by implementing executive approaches derived from business administration principles, which systematically heighten retrenchment pressures within liberal arts disciplines and non-commercial fields (How can educational institutions overcome the pitfalls of business models to manage academic goals through effective restructuring?, 2026). The research design therefore categorizes institutional documentary evidence across distinct analytical axes: formulaic metric exposure, which captures programmatic dependence on performance-weighted indicators, and administrative rationalization protocols, which identify how commercialized management models reframe academic units as cost centres. By mapping structural adjustments against funding alterations, this methodological framework isolates the transmission pathways between external formula mandates and internal academic closure risks. Combining documentary analysis of funding mandates with organizational restructuring records allows the evaluative model to assess systematic vulnerabilities across diverse disciplinary environments without conflating general fiscal strain with formula-driven rationalization practices.