This paper addresses the general problem of how to rationally choose an algorithm for phylogenetic inference. Specifically, the controversy between maximum likelihood (ML) and maximum parsimony (MP) perspectives is reframed within the philosophical issue of theory choice. A Kuhnian approach in which rationality is bounded and value-laden is offered and construed through the notion of a Style of Modeling. A Style is divided into four stages: collecting remnant models, constructing models of taxonomical identity, implementing modeling algorithms, and finally inferring and (...) confirming evolutionary trees or cladograms. The identification and investigation of styles is useful for exploring sociological and epistemological issues such as individuating scientific communities and assessing the rationality of algorithm choice. Regarding the last point, this paper suggests that the values motivating ML and MP perspectives are justified but only contextually; these algorithms also have normative force because they can be therapeutic by allowing us to rationally choose among several competing trees, nonetheless this force is limited and cannot be used in order to decide the controversy tout court. (shrink)

A scientific explanatory project, part-whole explanation, and a kind of science, part-whole science are premised on identifying, investigating, and using parts and wholes. In the biological sciences, mechanistic, structuralist, and historical explanations are part-whole explanations. Each expresses different norms, explananda, and aims. Each is associated with a distinct partitioning frame for abstracting kinds of parts. These three explanatory projects can be complemented in order to provide an integrative vision of the whole system, as is shown for a detailed case study: (...) the tetrapod limb. My diagnosis of part-whole explanation in the biological sciences as well as in other domains exploring evolved, complex, and integrated systems (e.g., psychology and cognitive science) cross-cuts standard philosophical categories of explanation: causal explanation and explanation as unification. Part-whole explanation is itself one essential aspect of part-whole science. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Abstract“Trait” is a ubiquitous term in biology, but its precise meaning and theoretical foundations remain opaque. After distinguishing between “trait” and “character,” I argue for the value of adopting Theodosius Dobzhansky’s 1956 definition and framework for understanding “trait,” which holds that traits are just “semantic devices” that artificially impose order on continuous biological phenomena. I elaborate on this definition to distinguish between trait validity (compliance with Dobzhansky’s trait definition) and trait utility (usefulness of a trait). As a consequence of this (...) elaboration of the meaning of “trait,” it becomes clear that considerations of adaptation, function, homogeneity and natural kinds have clouded discussions of the meaning of “trait” per se. Combining this account with work by David Hull and examples from contemporary biology, I demonstrate that even broad or heterogeneous traits (including multiple sub-traits) can qualify as valid and useful. As a test case for this understanding of trait, I show how it can help resolve critiques of schizophrenia’s status as a single trait, highlighting the recent advances made within schizophrenia research. (shrink)

I respond to the bad lot argument in the context of biological systematics. The response relies on the historical nature of biological systematics and on the availability of pattern explanations. The basic assumption of common descent enables systematic methodology to naturally generate candidate explanatory hypotheses. However, systematists face a related challenge in the issue of character analysis. Character analysis is the central problem for contemporary systematics, yet the general problem of which it is a case—what counts as evidence?—has not been (...) adequately discussed by proponents of inference to the best explanation. Facing this problem is the price of adopting abductive methods. I sketch an account of how systematists approach the problem of evidence. (shrink)

Evo-Devo exhibits a plurality of scientific “cultures” of practice and theory. When are the cultures acting—individually or collectively—in ways that actually move research forward, empirically, theoretically, and ethically? When do they become imperialistic, in the sense of excluding and subordinating other cultures? This chapter identifies six cultures – three /styles/ (mathematical modeling, mechanism, and history) and three /paradigms/ (adaptationism, structuralism, and cladism). The key assumptions standing behind, under, or within each of these cultures are explored. Characterizing the internal structure of (...) the cultures is necessary for understanding how they collaborate or compete, and how they are fragmented or integrated, in the rich interdisciplinary /trading zone/ (Galison 1997) of Evo-Devo. Evo-Devo is an important example of how science can progress through a radical plurality of perspectives and cultures. (shrink)