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)

The dangers of character reification for cladistic inference are explored. The identification and analysis of characters always involves theory-laden abstraction—there is no theory-free “view from nowhere.” Given theory-ladenness, and given a real world with actual objects and processes, how can we separate robustly real biological characters from uncritically reified characters? One way to avoid reification is through the employment of objectivity criteria that give us good methods for identifying robust primary homology statements. I identify six such criteria and explore each (...) with examples. Ultimately, it is important to minimize character reification, because poor character analysis leads to dismal cladograms, even when proper phylogenetic analysis is employed. Given the deep and systemic problems associated with character reification, it is ironic that philosophers have focused almost entirely on phylogenetic analysis and neglected character analysis. (shrink)

The theory and practice of contemporary comparative biology and phylogeny reconstruction (systematics) emphasizes algorithmic aspects but neglects a concern for the evidence. The character data used in systematics to formulate hypotheses of relationships in many ways constitute a black box, subject to uncritical assessment and social influence. Concerned that such a state of affairs leaves systematics and the phylogenetic theories it generates severely underdetermined, we investigate the nature of the criteria of homology and their application to character conceptualization in the (...) context of transformationist and generative paradigms. Noting the potential for indeterminacy in character conceptualization, we conclude that character congruence (the coherence of character statements) relative to a hierarchy is a necessary, but not a sufficient, condition for phylogeny reconstruction. Specifically, it is insufficient due to the lack of causal grounding of character hypotheses. Conceptualizing characters as homeostatic property cluster natural kinds is in accordance with the empirical practice of systematists. It also accounts for the lack of sharpness in character conceptualization, yet requires character identification and re-identification to be tied to causal processes. (shrink)

Deduction leads to causal explanation in phylogenetic inference when the evidence, the systematic character, is conceptualized as a transformation series. Also, the deductive entailment of modus tollens is satisfied when those kinds of events are operationalized as patristic difference. Arguments to the contrary are based largely on the premise that character-states are defined intensionally as objects, in terms of similarity relations. However, such relations leave biologists without epistemological access to the causal explanation and explanatory power of historical statements. Moreover, the (...) prediction-making to which those kinds of relations are limited in practice can lead to a category error—the mental conversion of an abstraction into a thing . The latter practices and problems characterize pattern cladistics, taxa being interpreted as homeostatic property cluster natural kinds, and other instrumentalist research programs. (shrink)

Most cognitive scientists nowadays tend to think that at least some of the mind’s capacities are the product of biological evolution, yet important conceptual problems remain for all scientists in order to be able to speak coherently of mental or cognitive systems as having evolved naturally. Two of these important problems concern the articulation of adequate, interesting, and empirically useful concepts of homology and variation as applied to cognitive systems. However, systems in cognitive science are usually understood as functional systems (...) of some sort. Thus, to be able to talk about functional systems being homologous requires having a solid, adequate, and empirically articulated concept of functional homology—and the same is true about functional variation. Here I construct an original concept of functional homology that, in my view, adequately systematizes a number of actual uses of the word “functional homology” in a variety of biological disciplines and in ethology. I also propose a number of criteria for the empirical application of the concept that are analogous to the criteria that are currently used in comparative biology, ethology, and molecular developmental genetics. Then I construct a concept of functional variation on the basis of this concept of homology. (shrink)

There is an argument that has recently been deployed in favor of thinking that the mind is mostly (or even exclusively) composed of cognitive modules; an argument that draws from some ideas and concepts of evolutionary and of developmental biology. In a nutshell, the argument concludes that a mind that is massively composed of cognitive mechanisms that are cognitively modular (henceforth, c-modular) is more evolvable than a mind that is not c-modular (or that is scarcely c-modular), since a cognitive mechanism (...) that is c-modular is likely to be biologically modular (henceforth, b-modular), and b-modular characters are more evolvable (e.g., Sperber 2002, Carruthers 2005). In evolutionary biology, the evolvability of a character in an organism is understood as the “organism’s capacity to facilitate the generation of non-lethal selectable phenotypic variation from random mutation” with respect to that character. Here I will argue that the notion of cognitive modularity needed to make this argument plausible will have to be understood in terms of the biological notion of variational independence; that is, it will have to be understood in such a way that a cognitive feature is c-modular only if few or no other morphological changes (cognitive and not) are significantly correlated with variations of that feature arising in members of the relevant population. I will also argue that all –except for (possibly) one—of the connotations contained in a cluster of notions of cognitive modularity widely accepted in some of the mainstream currents of thought in classical cognitive science, are simply irrelevant to the argument. In order to argue for this, I will have to examine the question as to whether there are any strong theoretical connections between (1) those connotations and (2) notions of modularity accepted in biology, specially in evolutionary and in developmental biology, that are thought to be most relevant to arguments to the effect that biological modularity enhances evolvability. (shrink)