New Frameworks for Unification|
Is unification truly dead? For many, explanatory division of labor in the special sciences has triumphed, and pluralist perspectives have eclipsed efforts to understand the unity of science. Historians and philosphers of biology seem to agree that evolutionary biology, in particular, is not a unified science, and that the evolutionary synthesis was not a conceptual synthesis, so much as an institutional synthesis. Reduction of genes to molecular properties likewise remains controversial. However, it is not clear that there is consensus about what it means for a theory to be unified. M. Morrison's (2000) recent work on unification and explanation serves as a starting point for discussion. This then opens to wider reinterpretation of interfield relationships and non-reductionist approaches to unification.
Organized by: Anya Plutynski
- Daniel Sirtes, Uniiveristy Hannover
"Explanation, Functional Reduction and Genes"
- According to Morrison (2000), unification of scientific theories may consist in a reduction of two phenomena to one, or it may involve integrating different phenomena into the same theory, that is, a synthetic unity in which two processes remain distinct but characterizable by the same theoretical framework (p.107). However, the mechanisms responsible for unifying may contribute nothing to the theory's explanatory power. In this way she decouples unification from explanation.
The functional model of reduction proposed by Kim (Mind in a Physical World, 2000) attempts to show how the mental could be equated with, and explained by, the physical. Kim's account treats the mental as a concept, not a property, which may be functionally reduced through a specification of its causal consequences. Such a functional reduction would explain mental concepts by identifying them with physical properties unifying our understanding of mental and physiological states. I will discuss Kim's account, which he exemplifies with the reduction of the gene concept in light of Morrison's challenges to our understanding of unification and explanation and their relation as they have occurred in the historical development of genetics.
- Anya Plutynski, University of Pennsylvania
"Saving Unification: A Reply to Morrison"
- Margaret Morrison has recently (2000) used Wright and Fisher, two population geneticists working in the 1920's and 30's, as a case study in support of her argument that a unification and explanation are often at odds in science. In particular, she argued that while the two offered a unified mathematical theory of evolution, they offered competing explanations of the mode of evolution. This paper takes a close look at the problems Fisher v. Wright were setting out to solve, and argues to the contrary that this may be one case where explanation and unification are not at odds in science.
- Todd Grantham, College of Charleston
"How Should We Conceptualize Unity When Reduction Fails?"
- Anti-reductionism remains the favored (although not universally accepted) view within the philosophy of biology. The failure of reductionism has led some (e.g., Dupre) to embrace a strong thesis of "disunity." However, even when reduction fails, two theories or fields can be unified (integrated) in significant ways. This paper lays out a general framework for conceptualizing unity that builds on the non-reductionistic models of unity put forward by Darden and Maull, Kitcher, and Kincaid. I argue that unity should be understood as a relationship between fields: two fields become more integrated as the number and significance of inter-field connections grow. I highlight two largely independent dimensions of unification. Fields are theoretically unified to the extent that we understand how the ontologies, concepts, and generalizations of these fields are connected. (Reductionism is a particularly strong form of theoretical unity, but not the only form of theoretical unity.) Fields are practically unified through heuristic connections (i.e., using the data or heuristics of one field to generate hypotheses in another field) and the sharing of data (e.g., using the data of other fields to test hypotheses). I present several examples drawn from biological sciences which illustrate the utility of this alternative conception of unity.
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