Transcending General Linear Reality

This paper argues that the dominance of linear models has led many sociologists to construe the social world in terms of a general linear reality. This reality assumes (1) that the social world consists of fixed entities with variable attributes, (2) that cause cannot flow from small to large attributes/events, (3) that causal attributes have only one causal pattern at once, (4) that the sequence of events does not influence their outcome, (5) that the careers of entities are largely independent, and (6) that causal attributes are generally independent of each other. The paper discusses examples of these assumptions in empirical work, considers standard and new methods addressing them, and briefly explores alternative models for reality that employ demographic, sequential, and network perspectives.