Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in (...) scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a decision enforced by an ethos as well as by an epistemology. As Daston and Galison argue, atlases shape the subjects as well as the objects of science. To pursue objectivity--or truth-to-nature or trained judgment--is simultaneously to cultivate a distinctive scientific self wherein knowing and knower converge. Moreover, the very point at which they visibly converge is in the very act of seeing not as a separate individual but as a member of a particular scientific community. Embedded in the atlas image, therefore, are the traces of consequential choices about knowledge, persona, and collective sight. Objectivity is a book addressed to anyone interested in the elusive and crucial notion of objectivity-- and in what it means to peer into the world scientifically. Lorraine Daston is Director at the Max Planck Institute for the History of Science in Berlin, Germany. She is the coauthor of Wonders and the Order of Nature, 1150-1750 and the editor of Things That Talk: Object Lessons from Art and Science. Peter Galison is Pellegrino University Professor of the History of Science and of Physics at Harvard University. He is the author of Einstein's Clocks, Poincaré's Maps: Empires of Time, How Experiments End, and Image and Logic: A Material Culture of Microphysics, and other books, and coeditor of The Architecture of Science. (shrink)

This 1983 book is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about (...) realism. Hacking illustrates how experimentation often has a life independent of theory. He argues that although the philosophical problems of scientific realism can not be resolved when put in terms of theory alone, a sound philosophy of experiment provides compelling grounds for a realistic attitude. A great many scientific examples are described in both parts of the book, which also includes lucid expositions of recent high energy physics and a remarkable chapter on the microscope in cell biology. (shrink)

This book exhibits deep philosophical quandaries and intricacies of the historical development of science lying behind a simple and fundamental item of common sense in modern science, namely the composition of water as H2O. Three main phases of development are critically re-examined, covering the historical period from the 1760s to the 1860s: the Chemical Revolution, early electrochemistry, and early atomic chemistry. In each case, the author concludes that the empirical evidence available at the time was not decisive in settling the (...) central debates and therefore the consensus that was reached was unjustified or at least premature. This leads to a significant re-examination of the realism question in the philosophy of science and a unique new advocacy for pluralism in science. Each chapter contains three layers, allowing readers to follow various parts of the book at their chosen level of depth and detail. The second major study in "complementary science", this book offers a rare combination of philosophy, history and science in a bid to improve scientific knowledge through history and philosophy of science. (shrink)

This article explores the characteristics of research sites that scientists have called “natural experiments” to understand and develop usable distinctions for the social sciences between “Nature’s or Society’s experiments” and “natural experiments.” In this analysis, natural experiments emerge as the retro-fitting by social scientists of events that have happened in the social world into the traditional forms of field or randomized trial experiments. By contrast, “Society’s experiments” figure as events in the world that happen in circumstances that are already sufficiently (...) “controlled” to be open for direct analysis without reconstruction work. (shrink)

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine (...) the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.Keywords: Experimental organism; Genetics; Model organism; Modeling; Philosophy of biology; Representation. (shrink)

The article reevaluates the reception of Mendelism in France, and more generally considers the complex relationship between Mendelism and plant breeding in the first half on the 20th century. It shows on the one side that agricultural research and higher education institutions have played a key role in the development and institutionalization of genetics in France, whereas university biologists remained reluctant to accept this approach on heredity. But on the other side, plant breeders, and agricultural researchers, despite an interest in (...) Mendelism, never came to see it as the breeders' panacea, and regarded it instead as of only limited value for plant breeding. I account for this judgment in showing that the plant breeders and Mendelism designed two contrasting kinds of experimental systems and inhabited distinct experimental cultures. While Mendelian geneticists designed experimental systems that allowed the production of definite ratios of different forms that varied in relation to a few characters, plant breeders' experimental systems produced a wide range of variation, featuring combinations between hundreds of traits. Rather than breaking this multiple variation down into simple elements, breeders designed and monitored a genetic lottery. The gene was a unit in a Mendelian experimental culture, an "epistemic thing" as Rheinberger put it, that could be grasped by means of statistical regularities, but it remained of secondary importance for French plant breeders, for whom the strain or the variety -- not the gene -- was the fundamental unit of analysis and manipulation. (shrink)

This paper presents and discusses a series of hybridization experiments carried out by Nils Herman Nilsson-Ehle between 1900 and 1907 at a plant breeding station in Svalöf, Sweden. Since the late 1880s, the Svalöf station had been renowned for its ‘scientific’ breeding methods, which basically consisted of an elaborate system of record-keeping through which the offspring of individual plants were traced over generations while being meticulously described. This record system corresponded to a certain breeding technique and certain theoretical convictions . (...) Inspired by Tschermack’s translation of Mendel’s Pisum-paper, Nilsson-Ehle began his experiments in 1900 and published a first, major synthesis of his findings in 1908. If one compares these experiments as documented in the breeding records, with their representations in print, one encounters discrepancies in terms of procedure and presentation of data. This can be explained by the fact that Nilsson-Ehle was obliged to follow the recording and breeding procedures institutionalised at Svalöf, and these procedures, grounded in a taxonomic discourse, left little room for Mendelian hybridisation experiments. The twists and turns that this story takes are analysed in terms of Bachelardian philosophy of science, where the ‘epistemological obstacle’ functions as a central, analytic category. In contrast to Bachelard, however, I will characterise these obstacles as being of an institutional, rather than mental, nature. Thus characterized, moreover, they turn out to have been prerequisites as much as barriers to scientific progress. (shrink)

What kinds of evidence reliably support predictions of effectiveness for health and social care interventions? There is increasing reliance, not only for health care policy and practice but also for more general social and economic policy deliberation, on evidence that comes from studies whose basic logic is that of JS Mill's method of difference. These include randomized controlled trials, case–control studies, cohort studies, and some uses of causal Bayes nets and counterfactual-licensing models like ones commonly developed in econometrics. The topic (...) of this paper is the 'external validity' of causal conclusions from these kinds of studies. We shall argue two claims. Claim, negative: external validity is the wrong idea; claim, positive: 'capacities' are almost always the right idea, if there is a right idea to be had. If we are right about these claims, it makes big problems for policy decisions. Many advice guides for grading policy predictions give top grades to a proposed policy if it has two good Mill's-method-of difference studies that support it. But if capacities are to serve as the conduit for support from a method-of-difference study to an effectiveness prediction, much more evidence, and much different in kind, is required. We will illustrate the complexities involved with the case of multisystemic therapy, an internationally adopted intervention to try to diminish antisocial behaviour in young people. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Advocates of “Mendelism” early on stressed the usefulness of Mendelian principles for breeders. Ever since, that usefulness—and the favourable opinion of Mendelism it supposedly engendered among breeders—has featured in explanations of the rapid rise of Mendelian genetics. An important counter-tradition of commentary, however, has emphasized the ways in which early Mendelian theory in fact fell short of breeders’ needs. Attention to intellectual property, narrowly and broadly construed, makes possible an approach that takes both the tradition and the counter-tradition seriously, by (...) enabling a more complete description of the theory-reality shortfall and a better understanding of how changing practices, on and off the Mendelians’ experimental farms, functioned to render that shortfall unproblematic. In the case of plant breeding in Britain, a perennial source of lost profits and disputes over ownership was the appearance of individual plants departing from their varietal types—so-called “rogues.” Mendelian plant varieties acquired a reputation for being rogue-free, and so for demonstrating the correctness of Mendelian principles , at a time when Mendelians were gradually taking control of the means for distributing their varieties. Mendelian breeders protected their products physically from rogue-inducing contamination in such a way that when rogues did appear, the default explanation—that contamination had somehow occurred—ensured that there was no threat to Mendelian principles. (shrink)

ABSTRACT This essay presents an alternative to interpretations of laboratories as institutions for controlled investigation of nature that are either placeless or “set apart.” It historicizes the claim by showing how the meaning of “laboratory” has both changed and diversified over the last two centuries. Originally a laboratory could be a site of organic growth or material manufacture, but it can now be a specialized domain for technological development, educational training, or quality testing. The essay then introduces some contingencies of (...) geography and gender by showing how boundaries between laboratories and other spaces—especially domestic kitchens—could be permeable or nonexistent; importantly, some spaces served as experimental laboratories without ever being designated as such. A key corollary, however, is that there were limits to this permeability: not all social spaces could be turned consensually into laboratories, and laboratory users could be intolerant of certain imported technical cultures. (shrink)

In this powerful work of conceptual and analytical originality, the author argues for the primacy of the material arrangements of the laboratory in the dynamics of modern molecular biology. In a post-Kuhnian move away from the hegemony of theory, he develops a new epistemology of experimentation in which research is treated as a process for producing epistemic things. A central concern of the book is the basic question of how novelty is generated in the empirical sciences. In addressing this question, (...) the author brings French poststructuralist thinking—notably Jacques Derrida’s concepts of “différance” and “historiality”—to bear on the construction of epistemic things. Historiographical perspective shifts from the actors’ minds to their objects of manipulation. These epistemological and historical issues are illuminated in a detailed case study of a particular laboratory, that of the oncologist and biochemist Paul C. Zamecnik and his colleagues, located in a specific setting—the Collis P. Huntington Memorial Hospital of Harvard University at the Massachusetts General Hospital of Boston. The author traces how, between 1945 and 1965, this group developed an experimental system for synthesizing proteins in the test tube that put Zamecnik’s research team at the forefront of those who led biochemistry into the era of molecular biology. (shrink)

Recent efforts to argue that nonepistemic values have a legitimate role to play in assessing scientific models, theories, and hypotheses typically either reject the distinction between epistemic and nonepistemic values or incorporate nonepistemic values only as a secondary consideration for resolving epistemic uncertainty. Given that scientific representations can legitimately be evaluated not only based on their fit with the world but also with respect to their fit with the needs of their users, we show in two case studies that nonepistemic (...) values can play a legitimate role as factors that override epistemic considerations in assessing scientific representations for practical purposes. (shrink)

The paper deals with the transformation of plant breeding from an agricultural practice into an applied academic science in the late 19th and early 20th centuries Germany. The aim is to contribute to the ongoing debate about the relationship between science and technology. After a brief discussion of this debate the first part of the paper examines how pioneers of plant breeding developed their breeding methods and commercially successful varieties. The focus here is on the role of scientific concepts and (...) theories in the agricultural innovation process. The second part turns towards the strategies by which agronomists tried to establish plant breeding as an academic discipline and themselves as the new experts for breeding research and varietal development. Again, the focus is on the interplay of scientific theory and agricultural practice. It is argued that in order to better understand the transformation of plant breeding into an applied academic science we have to take different levels into account, i.e. the levels of organizations, individuals and objects, at which science and technology interact. (shrink)

Critics of the ideal of value‐free science often assume that they must reject the distinction between epistemic and nonepistemic values. I argue that this assumption is mistaken and that the distinction can be used to clarify and defend the argument from inductive risk, which challenges the value‐free ideal. I develop the idea that the characteristic feature of epistemic values is that they promote, either intrinsically or extrinsically, the attainment of truths. This proposal is shown to answer common objections to the (...) distinction and provide a principled basis for separating legitimate from illegitimate influences of nonepistemic values in scientific inference. *Received June 2009; revised September 2009. †To contact the author, please write to: 503 S. Kedzie Hall, Michigan State University, East Lansing, MI 48824‐1032; e‐mail: [email protected]. (shrink)

Question the scientific method -- Different modes of experimentation -- Tirelessly tinkering with unruly conditions -- Practising experiments in a world of environmental concerns.

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. (...) Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods. (shrink)

In Landscapes and Labscapes Robert Kohler emphasized the separation between laboratory and field cultures and the creation of new "hybrid" or mixed practices as field sciences matured in the early twentieth century. This article explores related changes in laboratory practices, especially novel designs for the analysis of organism-environment relations in the mid-twentieth century. American ecologist Victor Shelford argued in 1929 that technological improvements and indoor climate control should be applied to ecological laboratories, but his recommendations were too ambitious for the (...) time. In the postwar period Frits W. Went, plant physiologist at the California Institute of Technology, created a new high-tech laboratory, dubbed a "phytotron", in the hope that it would transform plant sciences by allowing for unprecedented control of environmental variables. Went's aspirations, the research conducted in his laboratory, and its impact in initiating an international movement, are considered. Went's laboratory can be seen as a "hybrid culture" evolving in the laboratory, complementing and intersecting with some of the field practices that Kohler describes. It was also a countercultural movement against the reductionist trends of molecular biology in the 1950s and 1960s. By considering the history of the laboratory in relation to field sciences, we can explore how new funding sources and cross-disciplinary relations affected the development of field sciences, especially in the postwar period. (shrink)

ArgumentWe examine the criteria used to validate the use of nonhuman organisms in North-American alcohol addiction research from the 1950s to the present day. We argue that this field, where the similarities between behaviors in humans and non-humans are particularly difficult to assess, has addressed questions of model validity by transforming the situatedness of non-human organisms into an experimental tool. We demonstrate that model validity does not hinge on the standardization of one type of organism in isolation, as often the (...) case with genetic model organisms. Rather, organisms are viewed as necessarily situated: they cannot be understood as a model for human behavior in isolation from their environmental conditions. Hence the environment itself is standardized as part of the modeling process; and model validity is assessed with reference to the environmental conditions under which organisms are studied. (shrink)

The Empire of Chance tells how quantitative ideas of chance transformed the natural and social sciences, as well as daily life over the last three centuries. A continuous narrative connects the earliest application of probability and statistics in gambling and insurance to the most recent forays into law, medicine, polling and baseball. Separate chapters explore the theoretical and methodological impact in biology, physics and psychology. Themes recur - determinism, inference, causality, free will, evidence, the shifting meaning of probability - but (...) in dramatically different disciplinary and historical contexts. In contrast to the literature on the mathematical development of probability and statistics, this book centres on how these technical innovations remade our conceptions of nature, mind and society. Written by an interdisciplinary team of historians and philosophers, this readable, lucid account keeps technical material to an absolute minimum. It is aimed not only at specialists in the history and philosophy of science, but also at the general reader and scholars in other disciplines. (shrink)

ABSTRACT Historians of science, inasmuch as they are concerned with knowledges and practices rather than institutions, have tended of late to focus on case studies of common processes such as experiment and publication. In so doing, they tend to treat science as a single category, with various local instantiations. Or, alternatively, they relate cases to their specific local contexts. In neither approach do the cases or their contexts build easily into broader histories, reconstructing changing knowledge practices across time and space. (...) This essay argues that by systematically deconstructing the practices of science and technology and medicine (STM) into common, recurrent elements, we can gain usefully “configurational” views, not just of particular cases and contexts but of synchronic variety and diachronic changes, both short term and long. To this end, we can begin with the customary actors’ disciplines of early modern knowledge (natural philosophy, natural history, mixed mathematics, and experimental philosophy), which can be understood as elemental “ways of knowing and working,” variously combined and disputed. I argue that these same working knowledges, together with a later mode—synthetic experimentation and systematic invention—may also serve for the analysis of STM from the late eighteenth century to the present. The old divisions continued explicitly and importantly after circa 1800, but they were also “built into” an array of new sciences. This historiographic analysis can help clarify a number of common problems: about the multiplicity of the sciences, the importance of various styles in science, and the relations between science and technology and medicine. It suggests new readings of major changes in STM, including the first and second scientific revolutions and the transformations of biomedicine from the later twentieth century. It offers ways of recasting both microhistories and macrohistories, so reducing the apparent distance between them. And it may thus facilitate both more constructive uses of case studies and more innovative and acceptable longer histories. (shrink)

This paper outlines the contours of a historical geography of science. It begins by arguing for the relevance of spatially oriented histories of scientific thought and practice. The paper then considers three different historical geographies of science: those concerned with the places and spaces of science, those that detail the spatial contexts of scientific endeavour, and those that analyse the internal ‘cartographies’ of scientific theories and methods. The paper concludes with a discussion of other possible avenues of investigation in this (...) field.Scientific knowledge is made in a lot of different places. Does it matter where? Can the location of scientific endeavour make any difference to the conduct of science? And even more important, can it affect the content of science? In my view the answer to these questions is yes. (shrink)

It is customary to distinguish experimental from purely observational sciences. The former include physics and molecular biology, the latter astronomy and palaeontology. Experiments involve actively intervening in the course of nature, as opposed to observing events that would have happened anyway. When a molecular biologist inserts viral DNA into a bacterium in his laboratory, this is an experiment; but when an astronomer points his telescope at the heavens, this is an observation. Without the biologist’s handiwork the bacterium would never have (...) contained foreign DNA; but the planets would have continued orbiting the sun whether or not the astronomer had directed his telescope skyward. The observational/experimental distinction would probably be difficult to make precise 1, as the notion of an ‘intervention’ is not easily defined, but it is intuitively fairly clear, and is frequently invoked by scientists and historians of science. Experimentation, or ‘putting questions to nature’, is often cited as a hallmark of the modern scientific method, something that permitted the enormous advances of the last 350 years. And it is sometimes said that the social sciences lag behind the natural because controlled experiments cannot be done so readily in the former. Moreover in certain sciences, e.g. epidemiology, students are explicitly taught that experimental data is preferable to observational data, particularly for doing causal inference. So the distinction between observational and experimental science has quite wide currency, and is often regarded as methodologically significant. Surprisingly, mainstream philosophy of science has had rather little to say about the observational/experimental distinction. 2 For example, discussions of confirmation usually invoke a notion of ‘evidence’, to be contrasted with ‘theory’ or ‘hypothesis’; the aim is to understand how the evidence bears on the hypothesis. But whether this ‘evidence’ comes from observation or experiment generally plays no role in the discussion; this is true …. (shrink)

In the early twentieth century, Wilhelm Johannsen proposed his pure line theory and the genotype/phenotype distinction, work that is prized as one of the most important founding contributions to genetics and Mendelian plant breeding. Most historians have already concluded that pure line theory did not change breeding practices directly. Instead, breeding became more orderly as a consequence of pure line theory, which structured breeding programmes and eliminated external heritable influences. This incremental change then explains how and why the large multi-national (...) seed companies that we know today were created; pure lines invited standardisation and economies of scale that the latter were designed to exploit. Rather than focus on breeding practice, this paper examines the plant varietal market itself. It focusses upon work conducted by the National Institute of Agricultural Botany during the interwar years, and in doing so demonstrates that, on the contrary, the pure line was actually only partially accepted by the industry. Moreover, claims that contradicted the logic of the pure line were not merely tolerated by the agricultural geneticists affiliated with NIAB, but were acknowledged and legitimised by them. The history of how and why the plant breeding industry was transformed remains to be written. (shrink)

This paper examines the scientific controversy over the yields of genetically modified [GM] crops as a case study in epistemologically deep disagreements. Appeals to “the evidence” are inadequate to resolve such disagreements; not because the interlocutors have radically different metaphysical views (as in cases of incommensurability), but instead because they assume rival epistemological frameworks and so have incompatible views about what kinds of research methods and claims count as evidence. Specifically, I show that, in the yield debate, proponents and opponents (...) of GM crops cite two different sets of claims as evidence, which correspond to two rival epistemological frameworks, classical experimental epistemology and Nancy Cartwright's evidence for use. I go on to argue that, even if both sides of the debate accepted Cartwright's view, they might still disagree over what counts as evidence, because evidence for use ties standards of evidence to what is sometimes called the “context of application.”. (shrink)

The debate between the Mendelians and the (largely Darwinian) biometricians has been referred to by R. A. Fisher as ‘one of the most needless controversies in the history of science’ and by David Hull as ‘an explicable embarrassment’. The literature on this topic consists mainly of explaining why the controversy occurred and what factors prevented it from being resolved. Regrettably, little or no mention is made of the issues that figured in its resolution. This paper deals with the latter topic (...) and in doing so reorients the focus of the debate as one between Karl Pearson and R. A. Fisher rather than between the biometricians and the Mendelians. One reason for this reorientation is that Pearson's own work in 1904 and 1909 suggested that Mendelism and biometry could, to some extent, be made compatible, yet he remained steadfast in his rejection of Mendelism. The interesting question then is why Fisher, who was also a proponent of biometric methods, was able to synthesise the two traditions in a way that Pearson either could not or would not. My answer to this question involves an analysis of the ways in which different kinds of assumptions were used in modelling Mendelian populations. I argue that it is these assumptions, which lay behind the statistical techniques of Pearson and Fisher, that can be isolated as the source of Pearson's rejection of Mendelism and Fisher's success in the synthesis. (shrink)

Although many philosophers have employed the distinction between “direct” and “indirect” roles for values in science, I argue that it merits further clarification. The distinction can be formulated in several ways: as a logical point, as a distinction between epistemic attitudes, or as a clarification of different consequences associated with accepting scientific claims. Moreover, it can serve either as part of a normative ideal or as a tool for policing how values influence science. While various formulations of the distinction may (...) contribute to a normative ideal, they have limited effectiveness for regulating how values influence science. (shrink)

This paper discusses what it means and what it takes to integrate data in order to acquire new knowledge about biological entities and processes. Maureen O’Malley and Orkun Soyer have pointed to the scientific work involved in data integration as important and distinct from the work required by other forms of integration, such as methodological and explanatory integration, which have been more successful in captivating the attention of philosophers of science. Here I explore what data integration involves in more detail (...) and with a focus on the role of data-sharing tools, like online databases, in facilitating this process; and I point to the philosophical implications of focusing on data as a unit of analysis. I then analyse three cases of data integration in the field of plant science, each of which highlights a different mode of integration: inter-level integration, which involves data documenting different features of the same species, aims to acquire an interdisciplinary understanding of organisms as complex wholes and is exemplified by research on Arabidopsis thaliana; cross-species integration, which involves data acquired on different species, aims to understand plant biology in all its different manifestations and is exemplified by research on Miscanthus giganteus; and translational integration, which involves data acquired from sources within as well as outside academia, aims at the provision of interventions to improve human health and is exemplified by research on Phytophtora ramorum. Recognising the differences between these efforts sheds light on the dynamics and diverse outcomes of data dissemination and integrative research; and the relations between the social and institutional roles of science, the development of data-sharing infrastructures and the production of scientific knowledge. (shrink)

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the mathematician (...) and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher’s methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians’ tools and expertise into the station research programme. Fisher’s statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them. (shrink)

Over the past decade or so a number of historians of science and historical geographers, alert to the situated nature of scientific knowledge production and reception and to the migratory patterns of science on the move, have called for more explicit treatment of the geographies of past scientific knowledge. Closely linked to work in the sociology of scientific knowledge and science studies and connected with a heightened interest in spatiality evident across the humanities and social sciences this 'spatial turn ' (...) has informed a wide-ranging body of work on the history of science. This discussion essay revisits some of the theoretical props supporting this turn to space and provides a number of worked examples from the history of the life sciences that demonstrate the different ways in which the spaces of science have been comprehended. (shrink)

Prompted by recent recognitions of the omnipresence of horizontal gene transfer among microbial species and the associated emphasis on exchange, rather than isolation, as the driving force of evolution, this essay will reflect on hybridization as one of the central concerns of nineteenth-century biology. I will argue that an emphasis on horizontal exchange was already endorsed by ‘biology’ when it came into being around 1800 and was brought to full fruition with the emergence of genetics in 1900. The true revolution (...) in nineteenth-century life sciences, I maintain, consisted in a fundamental shift in ontology, which eroded the boundaries between individual and species, and allowed biologists to move up and down the scale of organic complexity. Life became a property extending both ‘downwards’, to the parts that organisms were composed of, as well as ‘upwards’, to the collective entities constituted by the relations of exchange and interaction that organisms engage in to reproduce. This mode of thinking was crystallized by Gregor Mendel and consolidated in the late nineteenth-century conjunction of biochemistry, microbiology and breeding in agro-industrial settings. This conjunction and its implications are especially exemplified by Wilhelm Johannsen’s and Martinus Beijerinck’s work on pure lines and cultures. An understanding of the subsequent constraints imposed by the evolutionary synthesis of the twentieth century on models of genetic systems may require us to rethink the history of biology and displace Darwin’s theory of natural selection from that history’s centre. (shrink)

ABSTRACT Historians of science, inasmuch as they are concerned with knowledges and practices rather than institutions, have tended of late to focus on case studies of common processes such as experiment and publication. In so doing, they tend to treat science as a single category, with various local instantiations. Or, alternatively, they relate cases to their specific local contexts. In neither approach do the cases or their contexts build easily into broader histories, reconstructing changing knowledge practices across time and space. (...) This essay argues that by systematically deconstructing the practices of science and technology and medicine (STM) into common, recurrent elements, we can gain usefully “configurational” views, not just of particular cases and contexts but of synchronic variety and diachronic changes, both short term and long. To this end, we can begin with the customary actors’ disciplines of early modern knowledge (natural philosophy, natural history, mixed mathematics, and experimental philosophy), which can be understood as elemental “ways of knowing and working,” variously combined and disputed. I argue that these same working knowledges, together with a later mode—synthetic experimentation and systematic invention—may also serve for the analysis of STM from the late eighteenth century to the present. The old divisions continued explicitly and importantly after circa 1800, but they were also “built into” an array of new sciences. This historiographic analysis can help clarify a number of common problems: about the multiplicity of the sciences, the importance of various styles in science, and the relations between science and technology and medicine. It suggests new readings of major changes in STM, including the first and second scientific revolutions and the transformations of biomedicine from the later twentieth century. It offers ways of recasting both microhistories and macrohistories, so reducing the apparent distance between them. And it may thus facilitate both more constructive uses of case studies and more innovative and acceptable longer histories. (shrink)