| I argue that philosophical accounts of scientific explanation appear to agree that identification of constraints is a significant feature of scientific explanation. Moreover, scientific explanations are evaluated according to how well they facilitate human prediction, manipulation and understanding of a given phenomena. The constraints identified in an explanation may be due to the physical states and structures as they are observed, as in the speed of light or the mass of the coffee mug on the table. These are physical constraints. Constraints also depend on the choices and perspectives of the individuals or communities producing and consuming the explanation. These latter constraints I refer to as framing constraints. Framing constraints include the choice to observe a biological organism within a particular eco-system as well as the choice to explain in the context of the observable universe. Ultimately, both physical constraints and framing constraints are not distinctive categories but extremes on a continuum.;Complex dynamical systems theory provides a framework for characterizing and understanding increases in system order in the context of certain constraints. Increases in system order entail increases in the observed correlations of spatial, temporal, or energetic features as represented by variations in a system's degrees of freedom. I argue that these increases in correlation length provide a basis for identifying characteristic scales of a system of interest that are larger than the scale defined in terms of the system's smallest components. In the context of scientific explanation, increases in order also result in the elimination of smallest scale degrees of freedom and their corresponding constraints. When the smallest scale degrees of freedom are eliminated from an explanation, the explanation is non-reductive. Given the proposed account of explanation in terms of constraints and insights regarding scale in terms of complex dynamical systems theory, I conclude that scientific explanations in the life and social sciences are sometimes non-reductive and multi-scale. |
