The social sciences and humanities have increasingly adopted computational terminology as the organizing categories for inquiry. We argue that by organizing research around vernacular computational objects (e.g. data, algorithms, or AI) and divided worldly domains (e.g. finance, health, and governance), scholars risk obscuring the universalizing practices and ambitions of computation. These practices seek to establish new relationalities at unprecedented scales, connecting disparate domains, circulating resources across boundaries, and positioning computational interventions as universally applicable. Drawing on intellectual traditions that inspect the fixity of universalizing claims, we problematize the easy adoption of computational categories and argue that they serve as epistemic traps that naturalize the expanding reach of computational universalism. Instead of accepting the hardened categories of our interlocutors, we propose attending to the partial, effortful, and often contested work of translation and commensuration that enables computational actors to position themselves as obligatory passage points across all domains. This approach reveals not only the remarkable achievements of computational relationalities at scale but also their exclusions, betrayals, and partialities. Our intervention aims to spur perspectives that examine how computational actors parse both technical objects and social worlds to advance universalizing ambitions while simultaneously obscuring the enormous labor required to maintain these divisions and connections.