Ingo Brigandt

This chapter offers a critique of intelligent design arguments against evolution and a philosophical discussion of the nature of science, drawing several lessons for the teaching of evolution and for science education in general. I discuss why Behe’s irreducible complexity argument fails, and why his portrayal of organismal systems as machines is detrimental to biology education and any under-standing of how organismal evolution is possible. The idea that the evolution of complex organismal features is too unlikely to have occurred by random mutation and selection (as recently promoted by Dembski) is very widespread, but it is easy to show students why such small probability arguments are fallacious. While intelligent design proponents have claimed that the exclusion of supernatural causes mandated by scientific methods is dogmatically presupposed by science, scientists have an empirical justification for using such methods. This justification is instructive for my discussion of how to demarcate science from pseudoscience. I argue that there is no universal account of the nature of science, but that the criteria used to judge an intellectual approach vary across historical periods and have to be specific to the scientific domain. Moreover, intellectual approaches have to be construed as practices based on institutional factors and values, and to be evaluated in terms of the activities of their practitioners. Science educators should not just teach scientific facts, but present science as a practice and make students reflect on the nature of science, as this gives them a better appreciation of the ways in which intelligent design falls short of actual science.

The concept of developmental constraint was at the heart of developmental approaches to evolution of the 1980s. While this idea was widely used to criticize neo-Darwinian evolutionary theory, critique does not yield an alternative framework that offers evolutionary explanations. In current Evo-devo the concept of constraint is of minor importance, whereas notions as evolvability are at the center of attention. The latter clearly defines an explanatory agenda for evolutionary research, so that one could view the historical shift from ‘developmental constraint’ towards ‘evolvability’ as the move from a concept that is a mere tool of criticism to a concept that establishes a positive explanatory project. However, by taking a look at how the concept of constraint was employed in the 1980s, I argue that developmental constraint was not just seen as restricting possibilities (‘constraining’), but also as facilitating morphological change in several ways. Accounting for macroevolutionary transformation and the origin of novel form was an aim of these developmental approaches to evolution. Thus, the concept of developmental constraint was part of a positive explanatory agenda long before the advent of Evo-devo as a genuine scientific discipline. In the 1980s, despite the lack of a clear disciplinary identity, this concept coordinated research among paleontologists, morphologists, and developmentally inclined evolutionary biologists. I discuss the different functions that scientific concepts can have, highlighting that instead of classifying or explaining natural phenomena, concepts such as ‘developmental constraint’ and ‘evolvability’ are more important in setting explanatory agendas so as to provide intellectual coherence to scientific approaches. The essay concludes with a puzzle about how to conceptually distinguish evolvability and selection.

The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity.

Contributing to the recent debate on whether or not explanations ought to be differentiated from arguments, this article argues that the distinction matters to science education. I articulate the distinction in terms of explanations and arguments having to meet different standards of adequacy. Standards of explanatory adequacy are important because they correspond to what counts as a good explanation in a science classroom, whereas a focus on evidence-based argumentation can obscure such standards of what makes an explanation explanatory. I provide further reasons for the relevance of not conflating explanations with arguments (and having standards of explanatory adequacy in view). First, what guides the adoption of the particular standards of explanatory adequacy that are relevant in a scientific case is the explanatory aim pursued in this context. Apart from explanatory aims being an important aspect of the nature of science, including explanatory aims in classroom instruction also promotes students seeing explanations as more than facts, and engages them in developing explanations as responses to interesting explanatory problems. Second, it is of relevance to science curricula that science aims at intervening in natural processes, not only for technological applications, but also as part of experimental discovery. Not any argument enables intervention in nature, as successful intervention specifically presupposes causal explanations. Students can fruitfully explore in the classroom how an explanatory account suggests different options for intervention.

The philosophy of science that grew out of logical positivism construed scientific knowledge in terms of set of interconnected beliefs about the world, such as theories and observation statements. Nowadays science is also conceived of as a dynamic process based on the various practices of individual scientists and the institutional settings of science. Two features particularly influence the dynamics of scientific knowledge: epistemic standards and aims (e.g., assumptions about what issues are currently in need of scientific study and explanation). While scientific beliefs are representations of the world, scientific standards and aims are epistemic values. The relevance of epistemic aims and values for belief change has been previously recognized. My paper makes a similar point for scientific concepts, both by studying how an individual concept changes (in its semantic properties) and by viewing epistemic aims and values tied to individual concepts.

David Chalmers and Frank Jackson have promoted a strong program of conceptual analysis, which accords a significant philosophical role to the a priori analysis of concepts. They found this methodological program on an account of concepts using two-dimensional semantics. This paper argues that Chalmers and Jackson’s account of concepts, and the related approach by David Braddon-Mitchell, is inadequate for natural kind concepts as found in biology. Two-dimensional semantics is metaphysically faulty as an account of the nature of concepts and concept possession. It is also methodologically flawed as a guideline for how to study scientific concepts. Proponents of two-dimensional semantics are criticized for not taking seriously semantic variation between persons and for failing to adequately account for the rationality of semantic change. I suggest a more pragmatic approach to natural kind term meaning, arguing that the epistemic goal pursued by a term’s use is an additional semantic property.

This introduction to the special section on integration in biology provides an overview of the different contributions. In addition to motivating the philosophical significance of analyzing integration and interdisciplinary research, I lay out common themes and novel insights found among the special section contributions, and indicate how they exhibit current trends in the philosophical study of integration. One upshot of the contributed papers is that there are different aspects to and kinds of integration, so that rather than attempting to offer a universal construal of what integrations is, philosophers have to analyze in concrete cases in what respects particular aspects of scientific theorizing and/or practice are ‘integrative’ and how this instance of integration works and was achieved

The present discussion of sociobiological approaches to ethnic nepotism takes Pierre van den Berghe ʼs theory as a starting point. Two points, which have not been addressed in former analyses, are considered to be of particular importance. It is argued that the behavioral mechanism of ethnic nepotism—as understood by van den Berghe—cannot explain ethnic boundaries and attitudes. In addition, I show that van den Bergheʼs central premise concerning ethnic nepotism is in contradiction to Hamiltonʼs formula, the essential principle of kin selection theory. It is further discussed how other approaches that make reference to ethnic nepotism are related to van den Bergheʼs account and its problems. I conclude with remarks on the evolutionary explanation of ethnic phenomena.

By linking the concepts of homology and morphological organization to evolvability, this paper attempts to (1) bridge the gap between developmental and phylogenetic approaches to homology and to (2) show that developmental constraints and natural selection are compatible and in fact complementary. I conceive of a homologue as a unit of morphological evolvability, i.e., as a part of an organism that can exhibit heritable phenotypic variation independently of the organism’s other homologues. An account of homology therefore consists in explaining how an organism’s developmental constitution results in different homologues/characters as units that can evolve independently of each other. The explanans of an account of homology is developmental, yet the very explanandum is an evolutionary phenomenon: evolvability in a character-by-character fashion, which manifests itself in phylogenetic patterns as recognized by phylogenetic approaches to homology. While developmental constraints and selection have often been viewed as antagonistic forces, I argue that both are complementary as they concern different parts of the evolutionary process. Developmental constraints, conceived of as the presence of the same set of homologues across phenotypic change, pertain to how heritable variation can be generated in the first place (evolvability), while natural selection operates subsequently on the produced variation.