<p>Generalization is central to theory development in social sciences; yet it is often treated as a methodological byproduct rather than as an inferential problem. As a result, studies conducted in contextually bounded settings often make population-level or universal claims that exceed their theoretical scope and design capacities, thereby weakening the credibility of cumulative knowledge. This paper reframes generalization as a boundary-conditioned inferential process rather than a statistical extrapolation from samples to populations. Drawing on scholarship in the social sciences, research methodology, and the philosophy of science, we distinguish among multiple forms of generalization and diagnose recurring inferential failures stemming from misalignments among theory, boundary conditions, and research design. We then develop boundary-conditioned inference as a diagnostic and evaluative framework for assessing generalization claims, clarifying how authors, reviewers, and editors can identify whether theoretical claims are appropriately aligned with mechanisms, contextual boundaries, and research design choices. By relocating generalization from the periphery of limitations sections to the core of theory construction, the framework provides a more precise basis for assessing rigor and contribution in social sciences and clarifies how scholars should articulate the scope and warrant of their theoretical claims.</p>