Public education relies heavily on data to document stratified inputs and outcomes, and to design interventions aimed at reducing disparities. Yet despite the promise and prevalence of data-driven policies and practices, inequalities persist. Indeed, contemporary scholarship has begun to question whether and how processes such as quantification and commensuration contribute to rather than remediate inequality. Using the 2013 closure of 24 Philadelphia public schools as a case study, I employ a mixed-methods approach to illuminate quantification and commensuration as nuanced processes with contingent, dualistic, and paradoxical relationships to inequality. The quantified approach to selecting schools for closure predisposed poor and minority communities to institutional loss because academic underperformance, a key selection metric, was correlated with disadvantage. Paradoxically, academic performance measures, coupled with commensuration strategies, also enabled advocates to successfully overturn closure recommendations. I offer an evidentiary account of how quantification can perpetuate inequality, and I complicate prevailing understandings of quantification as a technology of power.