 Causal Explanations; Models; Explanations of Meaning; Narratives. The number of factors that affect the occurrence of most human phenomena is too large to comprehend or test in a single model. Investigators must therefore select a subset of causal factors to include in their models. This selection may be based on fit with the values and interests of the investigator (Longino 1990, 2001). These interests often reflect background social and moral judgments of blame, responsibility, and acceptability of change. Conservatives are more likely to study divorce and out-of-wedlock birth as causes of women’s poverty, whereas feminists are more likely to focus on other causes—for example, the exclusion of women from better-paid jobs, failures of state support for dependent-care work within the family, the weak bargaining power of women in marriage, and norms of masculinity that lead fathers to avoid significant participation in child-rearing. These causal explanations are not incompatible. Normative interests may also determine whether one models only main effects or also interaction effects on outcomes relevant to human welfare. A variable—say, a certain lifestyle—that has a positive main effect on a population may have a negative effect on some subpopulations. Whether one models and tests for such effects may depend on whether one believes that one lifestyle does or should fit all, or whether one values pluralism and ontological heterogeneity (Anderson 2004).