I investigate how theoretical assumptions, pertinent to different perspectives and operative during the modeling process, are central in determining how nature is actually taken to be. I explore two different models by Michael Turelli and Steve Frank of the evolution of parasite-mediated cytoplasmic incompatility, guided, respectively, by Fisherian and Wrightian perspectives. Since the two models can be shown to be commensurable both with respect to mathematics and data, I argue that the differences between them in the (1) mathematical presentation of (...) the models, (2) explanations, and (3) objectified ontologies stem neither from differences in mathematical method nor the employed data, but from differences in the theoretical assumptions, especially regarding ontology, already present in the respective perspectives. I use my "set up, mathematically manipulate, explain, and objectify" (SMEO) account of the modeling process to track the model-mediated imposition of theoretical assumptions. I conclude with a discussion of the general implications of my analysis of these models for the controversy between Fisherian and Wrightian perspectives. (shrink)

I motivate the concept of styles of scientific investigation, and differentiate two styles, formal and compositional. Styles are ways of doing scientific research. Radically different styles exist. I explore the possibility of the unification of biology and social science, as well as the possibility of unifying the two styles I identify. Recent attempts at unifying biology and social science have been premised almost exclusively on the formal style. Through the use of a historical example of defenders of compositional biological social (...) science, the Ecology Group at the University of Chicago from, roughly, the 1930s to the 1950s, I attempt to show the coherence and possibility, if not utility, of employing the compositional style to effect the synthesis of biology and social science. I also relate the efforts of the Ecology Group to those of investigators in the Sociology Department of the University of Chicago. In my conclusion, I discuss the usefulness both of employing the category of styles of scientific investigation in historical and philosophical studies of science, as well as the concept of compositionality in scientific studies. I end the paper with some tentative suggestions regarding the importance of compositionality for an analysis of human society. (shrink)

Paradoxically, explorers of the territory of consciousness seem to be studying consciousness out of existence, from inside the field of "consciousness studies". How? Through their love of the phenomenon/process, they have developed powerful single models or lenses through which to understand consciousness. But in doing so, they also seek to destroy the other /equally useful/ lenses. Our opportunity lies in halting the vendettas and cross-speakings/cross-fire. The imploration is to stop the dichotomous thinking and pernicious reification of single models, and instead (...) search for divisions of labor, complementarities, and legitimate redescriptions among the various extant models. In other words, what would happen if we reimagined the conceptual classifications of the various models of consciousness, classifications based on general philosophical dichotomies (e.g., representational/non-representational and individualist/non-individualist), as a variety of compatible and even complementary perspectives on the same complex phenomenon and process? What would happen if rather than dig in our heels vis-à-vis our favorite theory of consciousness, at the exclusion of all the others, we saw our perceived enemy as an actual, indeed necessary, friend-in-waiting? What would it take to see a battlefield as a collaborative opportunity, to see a promising pluralism rather than an endless state space of conflict? (shrink)

Understanding scientific modelling can be divided into two sub-projects: analysing what model-systems are, and understanding how they are used to represent something beyond themselves. The first is a prerequisite for the second: we can only start analysing how representation works once we understand the intrinsic character of the vehicle that does the representing. Coming to terms with this issue is the project of the first half of this chapter. My central contention is that models are akin to places and characters (...) of literary fictions, and that therefore theories of fiction play an essential role in explaining the nature of model-systems. This sets the agenda. Section 2 provides a statement of this view, which I label the fiction view of model-systems, and argues for its prima facie plausibility. Section 3 presents a defence of this view against its main rival, the structuralist conception of models. In Section 4 I develop an account of model-systems as imagined objects on the basis of the so-called pretence theory of fiction. This theory needs to be discussed in great detail for two reasons. First, developing an acceptable account of imagined objects is mandatory to make the fiction view acceptable, and I will show that the pretence theory has the resources to achieve this goal. Second, the term ‘representation’ is ambiguous; in fact, there are two very different relations that are commonly called ‘representation’ and a conflation between the two is the root of some of the problems that beset scientific representation. Pretence theory provides us with the conceptual resources to articulate these two different forms of representation, which I call p-representation and t-representation respectively. Putting these elements together provides us with a coherent overall picture of scientific modelling, which I develop in Section 5. (shrink)

This paper examines the famous doctrine that independent prediction garners more support than accommodation. The standard arguments for the doctrine are found to be invalid, and a more realistic position is put forward, that whether evidence supports or not a hypothesis depends on the prior probability of the hypothesis, and is independent of whether it was proposed before or after the evidence. This position is implicit in the subjective Bayesian theory of confirmation, and the paper ends with a brief account (...) of this theory, and answer to the principal objections to it. (shrink)

The thesis that scientists give greater weight to novel predictions than to explanations of known facts is tested against historical cases in physical science. Several theories were accepted after successful novel predictions but there is little evidence that extra credit was given for novelty. Other theories were rejected despite, or accepted without, making successful novel predictions. No examples were found of theories that were accepted primarily because of successful novel predictions and would not have been accepted if those facts had (...) been previously known. (shrink)

Much if not most recent literature in philosophy of biology concerns the extent to which biological theories conform to what is known as the "received" philosophical view of scientific theories, a descendant of the logical-empiricist view of theories. But the received view currently faces a competitor--a very different view of theories known as the "semantic" view. It is argued here that the semantic view is more sensitive to the nature and limitations of evolutionary theory than is the received view. In (...) particular, the semantic view better accomodates the fact that evolutionary theory is bound to change as a result of the evolutionary process itself. This unusual feature of evolutionary theory provides a good reason for reconsidering the received view and paying close attention to the semantic view. (shrink)

Do predictions of novel facts provide stronger evidence for a theory than explanations of old ones? Sometimes yes, sometimes no. Which obtains has nothing to do with whether the evidence is predicted or explained, but only with the selection procedure used to generate the evidence. This is demonstrated by reference to a series of hypothetical drug cases and to Heinrich Hertz's 1883 cathode ray experiments.

Debate about adaptationism in biology continues, in part because within “the” problem of assessing adaptationism, three distinct problems are mixed together. The three problems concern the assessment of three distinct adaptationist positions, each of which asserts the central importance of adaptation and natural selection to the study of evolution, but conceives this importance in a different way. As there are three kinds of adaptationism, there are three distinct "anti-adaptationist" positions as well. Or putting it more formally, there are three different (...) dimensions here, and strongly adaptationist views, strongly anti-adaptationist views, and moderate views are possible for each dimension. (shrink)

In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, I demonstrate (...) an important advantage my account has over other theories of scientific representation. All existing theories analyse scientific representation in terms of relations, such as similarity or denotation. By contrast, my account does not take representation in modelling to be essentially relational. For this reason, it can accommodate a group of models often ignored in discussions of scientific representation, namely models which are representational but which represent no actual object. (shrink)

Two families of mathematical methods lie at the heart of investigating the hierarchical structure of genetic variation in Homo sapiens: /diversity partitioning/, which assesses genetic variation within and among pre-determined groups, and /clustering analysis/, which simultaneously produces clusters and assigns individuals to these “unsupervised” cluster classifications. While mathematically consistent, these two methodologies are understood by many to ground diametrically opposed claims about the reality of human races. Moreover, modeling results are sensitive to assumptions such as preexisting theoretical commitments to certain (...) linguistic, anthropological, and geographic human groups. Thus, models can be perniciously reified. That is, they can be conflated and confused with the world. This fact belies standard realist and antirealist interpretations of “race,” and supports a pluralist conventionalist interpretation. (shrink)

The ontology of race is replete with moral, political, and scientific implications. This book chapter surveys proposals about the reality of race, distinguishing among three levels of analysis: biogenomic, biological, and social. The relatively homogeneous structure of human genetic variation casts doubt upon the practice of postulating distinct biogenomic races that might be mapped onto socially recognized race categories.

Propositions alone are not constitutive of science. But is the "non-propositional" side of science theoretically superfluous: must philosophy of science consider it in order to adequately account for science? I explore the boundary between the propositional and non-propositional sides of biological theory, drawing on three cases: Grinnell's remnant models of faunas, Wright's path analysis, and Weismannism's role in the generalization of evolutionary theory. I propose a picture of material model-building in biology in which manipulated systems of material objects function as (...) theoretical models. In each of the cases, material systems such as diagrams play important generative as well as presentational roles. (shrink)

This essay is a critical review of Sandra Harding's The Science Question in Feminism. Her text constitutes a monumental effort to capture an overview of recent feminist critique of science and to develop a feminist dialectical and materialist conception of the history of masculinist science. In this analysis of Harding's work, the organizing categories as well as the main assumptions of the text are reconstructed for closer examination within the context of modern feminist critique of science and feminist theory in (...) general. Although a postive review of Harding's text is presented, questions are raised concerning the adequacy of socialist feminist assumptions for such a project, the limitations of Harding's theorization of gender, and the appropriateness of "postmodernism" as a final category of residence. (shrink)

An important theme to have emerged from the new experimentalist movement is that much of actual scientific practice deals not with appraising full-blown theories but with the manifold local tasks required to arrive at data, distinguish fact from artifact, and estimate backgrounds. Still, no program for working out a philosophy of experiment based on this recognition has been demarcated. I suggest why the new experimentalism has come up short, and propose a remedy appealing to the practice of standard error statistics. (...) I illustrate a portion of my proposal using Galison's experimental narrative on neutral currents. (shrink)

Neyman-Pearson methods in statistics distinguish between Type I and Type II errors. Through rigid control of Type I error, the "null" hypothesis typically receives the benefit of the doubt. I compare philosophers' interpretations of this feature of Neyman-Pearson tests with interpretations given in statistics textbooks. The pragmatic view of the tests advocated by Neyman, largely rejected by philosophers, lives on in many textbooks. Birnbaum thought the pragmatic view has a useful "heuristic" role in understanding testing. I suggest that it may (...) have the opposite effect. (shrink)

Should we think of our universe as law-governed and “clockwork”-like or as disorderly and “soup”-like? Alternatively, should we consciously and intentionally synthesize these two extreme pictures? More concretely, how deterministic are the postulated causes and how rigid are the modeled properties of the best statistical methodologies used in the biological and behavioral sciences? The charge of this entry is to explore thinking about causation in the temporal evolution of biological and behavioral systems. Regression analysis and path analysis are simply explicated (...) with reference to a thought experiment of painting three universes (clockwork, soup, and conscious) useful for imagining our actual universe. Attention to historical, structural, and mechanistic explanatory perspectives broadens the palette of methodologies available for analyzing determinism in, and explanation of, biological and behavioral systems. Each justified methodology provides a partial perspective on complex reality. Is a total explanation of any system ever possible, and what would it require? (shrink)