Bridging Social Inequality Driven by Information Asymmetry in Selective College Admissions: A Design Proposal for the MEDALS Planning Score

Abstract

Robert Jew, Isabella Jew, and Jonathan H. Jiang

Selective colleges in the United States are frequently framed as engines of upward mobility, yet enrollment at the most selective institutions remains sharply stratified by family income. Prior research documents a persistent "undermatch" among high-achieving, low-income students and shows that relatively low-cost information and guidance interventions can meaningfully shift application and enrollment behavior. Building on this literature, we argue that a key mechanism sustaining inequality in admissions is information asymmetry: students vary widely in access to credible, actionable knowledge about holistic review, competitive positioning, and multi-year planning. This asymmetry can distort (1) application decisions (where to apply), (2) preparation and time allocation (what to prioritize during high school), and (3) narrative construction (how to communicate achievements and context). We propose MEDALS, a planning-oriented self-assessment that simulates core dimensions of holistic review to provide students with structured diagnostic feedback rather than probabilistic admission predictions. MEDALS decomposes competitiveness into five domains—Academic Achievements, Intellectual Pursuits, Service Leadership, Activities Experiences, and Personal Qualities —reported as an overall score and domain subscores. To support decision-making without claiming college-specific prediction, MEDALS benchmarks students against selectivity tiers of institutions using publicly available admissions statistics. We present the conceptual framework, design principles, and a validation agenda (content validity via expert review; construct validity via factor structure; and downstream impacts via randomized field evaluation) needed for responsible deployment.