Rasmus Grønfeldt Winther

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.

This article began as a review of a conference, organized by Gerhard Schlosser, entitled “Modularity in Development and Evolution.” The conference was held at, and sponsored by, the Hanse Wissenschaftskolleg in Delmenhorst, Germany in May, 2000. The article subsequently metamorphosed into a literature and concept review as well as an analysis of the differences in current perspectives on modularity. Consequently, I refer to general aspects of the conference but do not review particular presentations. I divide modules into three kinds: structural, developmental, and physiological. Every module fulfills none, one, or multiple functional roles. Two further orthogonal distinctions are important in this context: module-kinds versus module-variants-of-a-kind and reproducer versus nonreproducer modules. I review criteria for individuation of modules and mechanisms for the phylogenetic origin of modularity. I discuss conceptual and methodological differences between developmental and evolutionary biologists, in particular the difference between integration and competition perspectives on individualization and modular behavior. The variety in views regarding modularity presents challenges that require resolution in order to attain a comprehensive, rather than a piecemeal and fragmentary, evolutionary developmental biology.

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies.

Schaffner’s model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner’s model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical structures in theoretical biology. A reconstructed Schaffnerian model could therefore shed light on mathematical theory development in the biological sciences and on the epistemology of mathematical practices more generally. *Received November 2006; revised March 2009. †To contact the author, please write to: Philosophy Department, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064; e‐mail: [email protected].

Although epistasis is at the center of the Fisher-Wright debate, biologists not involved in the controversy are often unaware that there are actually two different formal definitions of epistasis. We compare concepts of genetic independence in the two theoretical traditions of evolutionary genetics, population genetics and quantitative genetics, and show how independence of gene action (represented by the multiplicative model of population genetics) can be different from the absence of gene interaction (represented by the linear additive model of quantitative genetics). The two formulations converge with weak selection but not with strong selection or, for multiple loci, when the aggregated interaction terms are not negligible. As a result of the different formulations of gene interaction, the presence or absence of linkage disequilibrium,/D/, does not necessarily indicate the presence or absence of fitness epistasis. Indeed, linkage disequilibrium is generated in ‘additive’ models in quantitative genetics whenever two (or more) loci experience simultaneous selection. As a research strategy, it is often practical, for theoretical or experimental reasons, to minimize gene interaction by assuming independence of gene action in regard to fitness, or by assuming linear additive effects of multiple loci on a phenotype. However, minimizing the role of epistasis in theoretical investigations hinders our understanding of the origins of diversity and the evolution of complex phenotypes.

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.

Tom Stoppard’s 1966 play (and 1990 movie) /Rosencrantz and Guildenstern are Dead/ is a metatext – as a text, it interprets, builds upon, and refers to another text, Shakespeare’s Hamlet. Similarly, David N. Reznick’s /The Origin then and now: An interpretative guide to the Origin of Species/ (Princeton UP, 2010) is also a metatext. In this review, I turn to the history of science to evaluate whether Reznick’s book shares three families of virtues with Stoppard’s play: (i) brevity and precision, (ii) intrigue and appeal, and (iii) a genuine value-add to the original.

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.

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.