A Mechanism-Based Planning Framework for Equitable and Merit-Preserving University Admissions
Admissions systems in many countries struggle to balance merit-based selection with equity objectives. Most existing approaches--categorical quotas, fragmented equity tracks, and opaque adjustments--lack transparent decision rules and operational coherence. This paper introduces the Adaptive Merit Framework (AMF), a mechanism-based architecture that combines an individual-level SES correction rule with a structured decision pipeline. AMF operates under a non-displacement constraint: regular admissions remain determined entirely by raw merit scores, and only applicants whose corrected performance exceeds the same threshold qualify as conditional admits. The framework is operationalized through a five-stage decision spine--input definition, indicator aggregation, equity calibration via a single parameter alpha, batch execution, and irreversible closure--eliminating institutional discretion throughout. An empirical application using PISA 2022 Korea data (N = 6,377) shows that AMF identifies 4-9 additional candidates exclusively from the bottom half of the SES distribution, all above the merit threshold, expanding admissions by fewer than 0.15% of the cohort. The results demonstrate that rule-based correction can recover suppressed high-merit individuals without displacing standard admits, providing a transparent and scalable alternative to discretionary equity interventions. Keywords: Mechanism design, Decision architecture, University admissions, Equity-efficiency tradeoff, Socioeconomic correction, Non-displacement