Rasmus Grønfeldt Winther

Richard Lewontin’s 1972 paper, “The Apportionment of Human Diversity,” troubled the concept of race by showing that only a small proportion of the overall genetic variance across human groups is accounted for by the racial categories inherited from early twentieth-century physical anthropology. Since Lewontin’s landmark paper, critics of the biological race concept have continued appealing to this and other studies of the apportionment of genetic variance among putative groups. But has the critique gone far enough? We demonstrate that Lewontin’s results should trouble population as much as they do race. Indeed, an apportionment can be evolutionarily meaningful only insofar as the apportionments are adequate summaries of the evolutionary history and dynamics of the relevant structured variation. By appealing to four different scenarios of evolutionary process—expressed in a quantitative genetic manner—we show that Lewontin’s results are consistent with radically different histories, including ones understood in racial terms. Lewontin’s apportionment figures thus underdetermine a plurality of distinct models, which racialize in particular ways. This methodology may thus constitute a kind of racial classification rather than undermining all such classification. In a nutshell, population genetics is not nearly as antiracist as many would have us believe. What if the apportionment of variation among racial groups is not, in the first instance, a meaningful exercise? We argue that the continued use of apportionment statistics based on populations of dubious ontological status is inimical to the development of an antiracist account of human variation. A good first step toward developing an antiracist science of human variation is to stop taking the racists’ categories for granted.

Maps and mapping raise questions about models and modeling and in science. This chapter archives map discourse in the founding generation of philosophers of science (e.g., Rudolf Carnap, Nelson Goodman, Thomas Kuhn, and Stephen Toulmin) and in the subsequent generation (e.g., Philip Kitcher, Helen Longino, and Bas van Fraassen). In focusing on these two original framing generations of philosophy of science, I intend to remove us from the heat of contemporary discussions of abstraction, representation, and practice of science and thereby see in a more distant and neutral light the many productive ways in which maps can stand in analytically for scientific theories and models. The chapter concludes by complementing the map analogy – i.e., a scientific theory is a map of the world – with a model analogy, viz., a scientific model is a vehicle for understanding.

Investigating the reality and significance of racial categories, Remapping Race in a Global Context examines the role of race in human genomics, biomedicine, and struggles for social justice around the world. In this book, biologists, anthropologists, historians, and philosophers inspect critical questions around the biological reality of race and how it has been understood in different national and regional contexts. The essays also examine debates on the usefulness of race in medical and epidemiological studies. With focus on the fields of human genomics and biomedicine, this book presents critical findings on whether and how race might be ethically and epistemologically justified in our age of personalized medicine, mass surveillance, and biased algorithms. The book will be of interest to researchers and advanced students in a broad range of scientific and humanistic disciplines, including biology, anthropology, geography, philosophy, cultural or community studies, critical race theory, and any field concerned with the deep racial dividing lines running across societies globally.

Reification is to abstraction as disease is to health. Whereas abstraction is singling out, symbolizing, and systematizing, reification is neglecting abstractive context, especially functional, historical, and analytical-level context. William James and John Dewey provide similar and nuanced arguments regarding the perils and promises of abstraction. They share an abstraction-reification account. The stages of abstraction and the concepts of “vicious abstractionism,” “/the/ psychologist’s fallacy,” and “the philosophic fallacy” in the works of these pragmatists are here analyzed in detail. For instance, in 1896 Dewey exposes various fallacies associated with reifying dualistic reflex arc theory. The conclusion prescribes treatments (pluralism and assumption archaeology) for de-reifying ill models (i.e., universalized, narrowed, and ontologized models) in contemporary scientific fields such as cognitive science and biology.

A. W. F. Edwards is one of the most influential mathematical geneticists in the history of the discipline. One of the last students of R. A. Fisher, Edwards pioneered the statistical analysis of phylogeny in collaboration with L. L. Cavalli-Sforza, and helped establish Fisher's concept of likelihood as a standard of statistical and scientific inference. In this book, edited by philosopher of science Rasmus Grønfeldt Winther, Edwards's key papers are assembled alongside commentaries by leading scientists, discussing Edwards's influence on their own research and on thinking in their field overall. In an extensive interview with Winther, Edwards offers his thoughts on his contributions, their legacy, and the context in which they emerged. This book is a resource both for anyone interested in the history and philosophy of genetics, statistics, and science, and for scientists seeking to develop new algorithmic and statistical methods for understanding the genetic relationships between and among species both extant and extinct.

The ocean terrain spanning the globe is vast and complex—far from an immense flat plain of mud. To map these depths accurately and wisely, we must understand how cartographic abstraction and generalization work both in analog cartography and digital GIS. This chapter explores abstraction practices such as selection and exaggeration with respect to mapping the oceans, showing significant continuity in such practices across cartography and contemporary GIS. The role of measurement and abstraction—as well as of political and economic power, and sexual and personal bias—in these sciences is illustrated by the biographies of Marie Tharp and Bruce Heezen, whose mapping of the Mid-Atlantic Ridge precipitated a paradigm shift in geology.

A map is not its territory. Taking a map too seriously may lead to pernicious reification: map and world are conflated. As one family of cases of such reification, I focus on maps exuding the omphalos syndrome, whereby a centred location on the map is taken to be the world navel of, for instance, an empire. I build on themes from my book _When Maps Become the World_, in which I analogize scientific theories to maps, and develop the tools of assumption archaeology and integration platforms. Here I argue that excavating assumptions helps fill cartographic silences, showing the limitations of perspectives often at war. Furthermore, integrating perspectives permits resisting imperial central or master images. A worthwhile future project would be a repository of world-navel maps, critically annotated with cultural context and imperial information. Mutual understanding may result from such an integration platform, perhaps implemented online or in a museum.

Map making and, ultimately, _map thinking_ is ubiquitous across literature, cosmology, mathematics, psychology, and genetics. We partition, summarize, organize, and clarify our world via spatialized representations. Our maps and, more generally, our representations seduce and persuade; they build and destroy. They are the ultimate record of empires and of our evolving comprehension of our world. This book is about the promises and perils of map thinking. Maps are purpose-driven abstractions, discarding detail to highlight only particular features of a territory. By preserving certain features at the expense of others, they can be used to reinforce a privileged position. _When Maps Become the World_ shows us how the scientific theories, models, and concepts we use to intervene in the world function as maps, and explores the consequences of this, both good and bad. We increasingly understand the world around us in terms of models, to the extent that we often take the models for reality. Winther explains how in time, our historical representations in science, in cartography, and in our stories about ourselves replace individual memories and become dominant social narratives—they become reality, and they can remake the world. Available on The University of Chicago Press website, etc.

It is important to understand the science underlying philosophical debates. In particular, careful reflection is needed on the scientific study of the origins of Homo sapiens, the division of current human populations into ethnicities, populations, or races, and the potential impact of genomics on personalized medicine. Genomic approaches to the origins and divisions of our species are among the most multi-dimensional areas of contemporary science, combining mathematical modeling, computer science, medicine, bioethics, and philosophy of biology. The best evidence suggests that we are a young species, with a cradle in Africa. While prejudice, misunderstanding, and violence grow in many corners of the world, our best genomic science suggests a deep biological connection among all peoples.

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?

It is illegitimate to read any ontology about "race" off of biological theory or data. Indeed, the technical meaning of "genetic variation" is fluid, and there is no single theoretical agreed-upon criterion for defining and distinguishing populations (or groups or clusters) given a particular set of genetic variation data. Thus, by analyzing three formal senses of "genetic variation"—diversity, differentiation, and heterozygosity—we argue that the use of biological theory for making epistemic claims about "race" can only seem plausible when it relies on the user’s own assumptions about race; the move from biological measures to claims about “race” inevitably amounts to a pernicious reification. We also excavate assumptions in the history of the technical discourse over the concept of "race" (e.g., Livingstone's and Dobzhansky's 1962 exchange, Edwards' 2003 response to Lewontin 1972, as well as contemporary discussions of cladistic "race", and "races" as clusters). We show that claims about the existence (or non-existence) of "race" are underdetermined by biological facts, methods, and theories. Biological theory does not force the concept of "race" upon us; our social discourse, social ontology, and social expectations do. We become prisoners of our abstractions at our own hands, and at our own expense.

All eyes are turned towards genomic data and models as the source of knowledge about whether human races exist or not. Will genomic science make the final decision about whether racial realism (e.g., racial population naturalism) or anti-realism (e.g., racial skepticism) is correct? We think not. We believe that the results of even our best and most impressive genomic technologies underdetermine whether bio-genomic races exist, or not. First, different sub-disciplines of biology interested in population structure employ distinct concepts, aims, measures, and models, producing cross-cutting categorizations of population subdivisions rather than a single, universal bio-genomic concept of "race." Second, within each sub-discipline (e.g., conservation biology, phylogenetics), genomic results are consistent with, and map multiply to, racial realism and anti-realism. Indeed, racial ontologies are constructed conventionally, rather than discovered. We thus defend a /constructivist conventionalism/ about bio-genomic racial ontology. Choices and conventions must always be made in identifying particular kinds of groups. Political agendas, social programs, and moral questions premised on the existence of naturalistic race must accept that no scientifically grounded racial ontology is forthcoming, and adjust presumptions, practices, and projects accordingly.

Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist in formulating predictions. Moving from their knowledge-producing representational functions to their interventional roles (Hacking 1983), theories are integral to building technologies used within consumer, industrial, and scientific milieus. This entry explores the structure of scientific theories from the perspective of the Syntactic, Semantic, and Pragmatic Views. Each of these views answers questions such as the following in unique ways. What is the best characterization of the composition and function of scientific theory? How is theory linked with world? Which philosophical tools can and should be employed in describing and reconstructing scientific theory? Is an understanding of practice and application necessary for a comprehension of the core structure of a scientific theory? How are these three views ultimately related?

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.

Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these two views with respect to four points regarding ontological assumptions: (1) the origin of ontological assumptions, (2) the relation of such assumptions to the formal models of the same theory, (3) their use in integrating and negotiating different formal models of distinct theories, and (4) their employment in explanatory activity. Dialectical is here used in both its Hegelian–Marxist sense of opposition and tension between alternative positions and in its Platonic sense of dialogue between advocates of distinct theories. I investigate three case studies, from Levins and Lewontin as well as from a recent paper of mine, that show the relevance and power of the dialectical understanding of theorizing and modeling.

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.

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.

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality.

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.

Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when styles of scientific research are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed and applied styles, paradigms, and models simultaneously? I address these questions in general and for a specific case study: a brief history of systematics.