Social scientists tend to cluster in groups that share methodological commitments. Formal theorists emphasize parsimony, precision, and logical coherence; more policy-relevant theorists tend to privilege richness, accuracy, and usefulness. Advocates of large-N statistical analysis place greater weight on generality, objectivity, and formal estimates of uncertainty; area studies scholars emphasize context-bounded generalizations and historical richness. Experimentalists prioritize clean (i.e., exogenous) treatment assignment and bounded but credible estimates of average causal effects; others prefer to study large thorny questions using designs that admittedly suffer from problematic biases. As more scholarly conversation take place within, rather than across, these methodological groupings, there is a risk that each group will come to h old its respective weighting of methodological criteria as superior and will forget the methodological trade-offs that led other domains of social science to prioritize other criteria.