My aim in this paper is to propose a way to study the role of perspectives in both the production and justification of experimental knowledge claims. My starting point for this will be Anjan Chakravartty’s claim that Ronald Giere’s perspectival account of the role of instruments in the production of such claims entails relativism in the form of irreducibly incompatible truths. This led Michela Massimi to argue that perspectivism, insofar as it wants to form a realist position, is only concerned (...) with the justification of such claims: whether they are produced reliably is, on her view, a perspective-independent fact of the matter. Following a suggestion by Giere on how scientists handle incompatible experimental results, I will then argue that Massimi’s perspectivism can be extended to also cover the production of such claims, without falling into relativism. I will elaborate this suggestion by means of Uljana Feest’s work on how scientists handle incompatible experimental results. I will argue that, if we reconceptualize perspectives as embodied and situated ways of going about in experimentation that can be made explicit through interpretation, we can obtain a fruitful understanding of the role of perspectives in both the production and justification of experimental knowledge. While this role is primarily exploratory, it can still allow for a substantial form of realism. (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

Models developed using machine learning are increasingly prevalent in scientific research. At the same time, these models are notoriously opaque. Explainable AI aims to mitigate the impact of opacity by rendering opaque models transparent. More than being just the solution to a problem, however, Explainable AI can also play an invaluable role in scientific exploration. This paper describes how post-hoc analytic techniques from Explainable AI can be used to refine target phenomena in medical science, to identify starting points for future (...) investigations of causal relationships, and to generate possible explanations of target phenomena in cognitive science. In this way, this paper describes how Explainable AI—over and above machine learning itself—contributes to the efficiency and scope of data-driven scientific research. (shrink)

I present an account of classical genetics to challenge theory-biased approaches in the philosophy of science. Philosophers typically assume that scientific knowledge is ultimately structured by explanatory reasoning and that research programs in well-established sciences are organized around efforts to fill out a central theory and extend its explanatory range. In the case of classical genetics, philosophers assume that the knowledge was structured by T. H. Morgan’s theory of transmission and that research throughout the later 1920s, 30s, and 40s was (...) organized around efforts to further validate, develop, and extend this theory. I show that classical genetics was structured by an integration of explanatory reasoning and investigative strategies . The investigative strategies, which have been overlooked in historical and philosophical accounts, were as important as the so-called laws of Mendelian genetics. By the later 1920s, geneticists of the Morgan school were no longer organizing research around the goal of explaining inheritance patterns; rather, they were using genetics to investigate a range of biological phenomena that extended well beyond the explanatory domain of transmission theories. Theory-biased approaches in history and philosophy of science fail to reveal the overall structure of scientific knowledge and obscure the way it functions.Author Keywords: Investigation; Genetic approach; Structure of knowledge; Classical genetics. (shrink)

My aim in this article is to introduce readers to the topic of exploratory experimentation and briefly explain how the three articles that follow, by Richard Burian, Kevin Elliott, and Maureen O'Malley, advance our understanding of the nature and significance of exploratory research. I suggest that the distinction between exploratory and theory-driven experimentation is multidimensional and that some of the dimensions are continuums. I point out that exploratory experiments are typically theory-informed even if they are not theory-driven. I also distinguish (...) between research programs and experiments. Research programs that are largely exploratory, such as the ones discussed in these case studies, can involve both exploratory and theory-driven experimentation. (shrink)

Driven by an appreciation of the field’s early stage of development, I apply the concept of exploratory experimentation, originally put forward in the late 90s philosophy of biology, to current research in cognitive neuroscience. I concentrate on functional magnetic resonance imaging and how this wide-spread technique is used, from experimental design to data analysis. I claim that, although subject to certain significant modifications with respect to the concept’s original rendering, the exploratory character of neuroimaging experiments can be appreciated considering their (...) goals, centered on the stabilization of experimental systems for phenomenological description, and the relevance of their methodological facet. Although I do not claim that there is a specific kind of experiment that one can single out as definitely exploratory, exploration can be seen as a general trait imbuing fMRI-based experimentation. (shrink)

I focus on the concept of the receptive field of a sensory neuron, taking it as a prominent case to address conceptual change in the history of neuroscience. I argue for an interpretation of its ro...

Starting with a discussion of what I call Koyré’s paradox of conceptual novelty, I introduce the ideas of Damerow et al. on the establishment of classical mechanics in Galileo’s work. I then argue that although the view of Damerow et al. on the nature of Galileo’s conceptual innovation is convincing, it misses an essential element: Galileo’s use of the experiments described in the first day of the Two New Sciences. I describe these experiments and analyze their function. Central to my (...) analysis is the idea that Galileo’s pendulum experiments serve to secure the reference of his theoretical models in actually occurring cases of free fall. In this way Galileo’s experiments constitute an essential part of the meaning of the new concepts of classical mechanics. (shrink)

Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

Computational modeling is one of the primary approaches to constructing protein–protein interfaces in the laboratory. The algorithm-driven computational protein design has been successfully applied to the construction of functional proteins with improved binding affinity and increased thermostability. It is intriguing how a computational protein modeling approach can construct and shape the reality of new functional proteins from scratch. I articulate an account of abstraction and exploration-driven strategies in this computational endeavor. I aim to show that how a computational modelling approach, (...) which is laden with mathematics and algorithms, can have a constructive force on the target protein. (shrink)

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...) targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

: The increasing attention on experiment in the last two decades has led to important insights into its material, cultural and social dimensions. However, the role of experiment as a tool for generating knowledge has been comparatively poorly studied. What questions are asked in experimental research? How are they treated and eventually resolved? And how do questions, epistemic situations, and experimental activity cohere and shape each other? In my paper, I treat these problems on the basis of detailed studies of (...) research practice. After presenting several cases from the history of electricity—Dufay, Ampère, and Faraday—I discuss a specific type of experiment—the "exploratory experiment"—and analyze how it works in concept formation. I argue that a fuller understanding of experiment can only be achieved by intertwining historical and philosophical perspectives in such a way that the very separation of the two become questioable. (shrink)

The standard view in current philosophy of creativity says that being creative has two requirements: being novel and being valuable. The standard view on creativity has recently become an object of critical scrutiny. Hills and Bird have specifically proposed to remove the value requirement from the definition, as it is not clear that creative objects are necessarily valuable or creative people necessarily praiseworthy. In this paper, I argue against Hills and Bird, since eliminating the element of value from the explanation (...) of creativity hinders the understanding of the role that creative products play in actual epistemic practices, which are fundamentally normative. More specifically, I argue that the terms ‘creativity’ and ‘creative’ function as thick epistemic concepts when employed by competent epistemic agents in practice, that is, these concepts have both a descriptive and an evaluative content that cannot be disentangled from one another. Accordingly, I suggest that philosophers should prefer thick accounts over thin accounts of creativity. A thick account of creativity is one that endorses the standard view at its basis, but further develops it in two ways: by stressing the entanglement of the value and novelty requirements; by permitting to encompass a range of domain-specific characterizations of such entanglement for different epistemic situations. In order to take the first steps in the development of such a thick account of creativity, I look at the domain of scientific practices as a case in point, and try to spell out what the thickness of creative instances typically entails here. Namely, I identify the worthy novelty of creative models and methods with their potential to clarify a tradition, with fruitfulness, and with the fulfilment of exploratory aims. (shrink)

Within science fiction the topic of ‘first contact’ is a popular theme. How will an encounter with aliens unfold? Will we succeed in communicating with them? Although such questions are present in the background of many science fiction novels, they are not always explicitly dealt with and even if so, often in a poor way. In this article, I will introduce a typology of five dominant types of solutions to the problem of first contact in science fiction works. The first (...) four solutions are the more dominant, but also the least interesting ones. There is a fifth category that addresses the question of first contact in a more interesting way, exemplified by the work of Stanisław Lem. This fifth option defines itself as a critique of the four previous categories, or of their shared assumption of what Lem (1967) has called ‘the myth of cognitive universality’. Lem is sceptical of the common optimism that first contact will always be successful. In books such as Solaris (1961), His Master’s Voice (1967) and Fiasco (1986), humanity makes first contact with an alien phenomenon, but fails to comprehend the phenomenon. Fundamentally, it will be argued that Lem’s work shows that in such an encounter we will typically not only lack the right answers to our questions, but that we also often lack the correct questions: we simply do not have the right categories or instruments to even recognize, let alone meaningfully interrogate, the alien phenomenon. The article ends with an exploration of the implications of Lem’s pessimism and whether it is the most plausible option for first contact. Moreover, the article will draw some lessons for philosophy of science, by exploring the parallel with the confrontation of novel or deviant phenomena in science. Lem’s work is helpful here because it succeeds in articulating what has not always been appreciated in the philosophy of science, namely that the right questions by which to interrogate scientific phenomena are not given, but that their articulation always requires work. (shrink)

It is now well-appreciated by philosophers that contemporary large-scale ‘-omics’ studies in biology stand in non-trivial relationships to more orthodox hypothesis-driven approaches. These relationships have been clarified by Ratti (2015); however, there remains much more to be said regarding how an important field of genomics cited in that work—‘genome-wide association studies’ (GWAS)—fits into this framework. In the present article, we propose a revision to Ratti’s framework more suited to studies such as GWAS. In the process of doing so, we introduce (...) to the philosophical literature novel exploratory experiments in (phospho)proteomics, and demonstrate how these experiments interplay with the above considerations. (shrink)

Scientists and philosophers generally agree that the replication of experiments is a key ingredient of good and successful scientific practice. “One-offs“ are not significant; experiments must be replicable to be considered valid and important. But the term “replication“ has been used in a number of ways, and it is therefore quite difficult to appraise the meaning and significance of replications. I consider how history may help - and has helped - with this task. I propose that: 1) Studies of past (...) scientific episodes in historical context and of recent philosophical contributions to the discussion are heuristic tools for exploring and clarifying the meaning of that concept. 2) The analysis of the development of the methodological imperative of replication sheds light on the significance scientists have attached to it, thereby contributing further to the clarification of the concept. 3) The analysis of the history of philosophical thought about methods and scientific methodology helps understand why philosophers have not paid much attention to the analysis of the concept of replication. (shrink)

This essay is a contribution to the history of methodological thought. I focus on key methodological criteria for successful experimentation, replication and multiple determinations of empirical evidence. Drawing on reports of experiments with viper venom from the late seventeenth and late eighteenth centuries, as well as on present-day methodological thought I examine whether past experimenters regarded repetition, replication, and multiple determinations as criteria for validity; what exactly they meant by this; what they hoped to gain by repeating, varying, triangulating, and (...) replicating; and how relevant these criteria were for them. I also consider if this analysis has implications for current philosophical work on the methodology of experimental practice. (shrink)

The thesis of theory-ladenness of observations, in its various guises, is widely considered as either ill-conceived or harmless to the rationality of science. The latter view rests partly on the work of the proponents of New Experimentalism who have argued, among other things, that experimental practices are efficient in guarding against any epistemological threat posed by theory-ladenness. In this paper I show that one can generate a thesis of theory-ladenness for experimental practices from an influential New Experimentalist account. The notion (...) I introduce for this purpose is the concept of ‘theory-driven data reliability judgments’, according to which theories which are sought to be tested with a particular set of data guide reliability judgments about those very same data. I provide various prominent historical examples to show that TDRs are used by scientists to resolve data conflicts. I argue that the rationality of the practices which employ TDRs can be saved if the independent support of the theories driving TDRs is construed in a particular way. (shrink)

Experimentation represents today a ‘hot’ topic in computing. If experiments made with the support of computers, such as computer simulations, have received increasing attention from philosophers of science and technology, questions such as “what does it mean to do experiments in computer science and engineering and what are their benefits?” emerged only recently as central in the debate over the disciplinary status of the discipline. In this work we aim at showing, also by means of paradigmatic examples, how the traditional (...) notion of controlled experiment should be revised to take into account a part of the experimental practice in computing along the lines of experimentation as exploration. Taking inspiration from the discussion on exploratory experimentation in the philosophy of science—experimentation that is not theory-driven—we advance the idea of explorative experiments that, although not new, can contribute to enlarge the debate about the nature and role of experimental methods in computing. In order to further refine this concept we recast explorative experiments as socio-technical experiments, that test new technologies in their socio-technical contexts. We suggest that, when experiments are explorative, control should be intended in a posteriori form, in opposition to the a priori form that usually takes place in traditional experimental contexts. (shrink)

This paper examines how scientists conceptualize their research methodologies. Do scientists raise concerns about vague criteria and genuine uncertainties in experimental practice? If so, what sorts of issues do they identify as problematic? Do scientists acknowledge the presence of value judgments in scientific research, and do they reflect on the relation between epistemic and non-epistemic criteria for decisionmaking? We present findings from an analysis of qualitative interviews with 63 scientific researchers who talk about their views on good research practice. We (...) argue that analysts of science should care about scientists’ conceptualizations of the criteria and of the practical judgments that scientific inquiry involves. While scientists’ accounts of their own research methodologies alone do not give us a full picture of how science really works, they can point us to areas of concern. They can inspire and direct philosophical reflections about how science works. Throughout the interviews, the participating researchers provided specific examples from their own research contexts as illustrations of their methodological points. These examples reveal that scientists often struggle to evaluate the quality of their data, to figure out whether the available evidence confirms their hypothesis, whether a replication was successful, or to what extent they can rely on peer-reviewed papers. General ideas about good research methods do not directly translate into specific evaluation criteria or strategies that can guide research and help validate empirical data. (shrink)

This paper examines how scientists conceptualize their research methodologies. Do scientists raise concerns about vague criteria and genuine uncertainties in experimental practice? If so, what sorts of issues do they identify as problematic? Do scientists acknowledge the presence of value judgments in scientific research, and do they reflect on the relation between epistemic and non-epistemic criteria for decisionmaking? We present findings from an analysis of qualitative interviews with 63 scientific researchers who talk about their views on good research practice. We (...) argue that analysts of science should care about scientists’ conceptualizations of the criteria and of the practical judgments that scientific inquiry involves. While scientists’ accounts of their own research methodologies alone do not give us a full picture of how science really works, they can point us to areas of concern. They can inspire and direct philosophical reflections about how science works. Throughout the interviews, the participating researchers provided specific examples from their own research contexts as illustrations of their methodological points. These examples reveal that scientists often struggle to evaluate the quality of their data, to figure out whether the available evidence confirms their hypothesis, whether a replication was successful, or to what extent they can rely on peer-reviewed papers. General ideas about good research methods do not directly translate into specific evaluation criteria or strategies that can guide research and help validate empirical data. (shrink)

This paper presents a case of severe uncertainty in the development of autonomous and intelligent systems in Artificial Intelligence and autonomous robotics. After discussing how uncertainty emerges from the complexity of the systems and their interaction with unknown environments, the paper describes the novel framework of explorative experiments. This framework presents a suitable context in which many of the issues relative to uncertainty, both at the epistemological level and at the ethical one, in this field should be reframed. The case (...) of autonomous robot systems for search and rescue is used to make the discussion more concrete. (shrink)

This article unearths little-studied accounts of the status and role of hypotheses in late eighteenth- and early nineteenth-century Germany. German thinkers regarded hypotheses, including those about unobservable causes for visible effects, as legitimate and necessary ingredients of scientific inquiry. They debated the nature of probable hypotheses resulting from inductions, proposed heuristics for making causal hypotheses, and advanced criteria for assessing and testing them. My survey of these rich and multifaceted discussions shows that many themes and topics that we commonly associate (...) with modern philosophy of science were discussed decades earlier by authors of educational and practice-oriented books on logic: consequential testing, underdetermination, auxiliary hypotheses, the problem of unobservable entities, fallibility, and elaborate methodologies of observation and experimentation. It also illuminates the long-term history of present-day criteria for hypothesis evaluation. (shrink)

Review essay of How to do science with models. A philosophical primer. Springer briefs in philosophy, Axel Gelfert., 129, Price € 49,99 softcover, ISBN: 978-3-319-27954-1.

Much has been written on Claude Bernard as a relentless promoter of the experimental method in physiology. Although the paper will touch Bernard’s experimental intuitions and his experimental practice as well, its focus is slightly different. It will address the laboratory, that is, the space in which experimentation in the life sciences takes place, and it will analyze the scattered remarks that Bernard made on the topic both in his books and in his posthumously published writings. The paper is divided (...) into four parts. The introduction briefly sketches the coming into being of the physiological laboratory in the first half of the nineteenth century. The second section will give an overview of Claude Bernard’s own itinerary in physiology and his personal laboratory experience. The third part of the paper will have a look at the image of the laboratory that Claude depicted in his Introduction to Experimental Medicine. In the subsequent section and by contrast, the image of the laboratory will come into focus as it can be reconstructed from Bernard’s notebook that he kept between 1850 and 1860, the Cahier rouge. Finally, the fifth part of the paper will spotlight Claude Bernard’s comparison of the sciences and the arts and their respective practices. A brief concluding statement tries to summarize Bernard’s epistemological position toward experimentally practiced science. (shrink)

Recently, biologists have argued that data - driven biology fosters a new scientific methodology; namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data - driven studies can be included into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...) generalizations to complement the procedure of prioritization. Overall this paper aims to shed light on the structure of contemporary research in molecular biology. (shrink)

The 1980s, it is often claimed, was the decade when experimentation finally became a philosophical topic. This was the responsibility, the claim continues, of one particular movement within philosophy of science, called “new experimentalism.” The aim of this article is to complicate this historical narrative. We argue that in the 1980s, the study of experimentation was carried out not by one movement with one particular aim but rather in a diverse and open-ended way by people with different aims and backgrounds. (...) We then argue that from the late 1990s onward, this diversity disappeared and made room for disciplinary divisions—questions concerning experimentation became philosophical, others sociological, and so on. The reason for this, we claim, was that science and technology studies, philosophy of technology, and philosophy of science took over aspects of the 1980s study of experimentation. In this way, we argue, these elements became institutionalized, whereas others were forgotten. The importance of this process of institutionalization is illustrated by means of a discussion of other, similar approaches to the philosophy of experimentation that have not been able to ensure continuity because they did not find an institutional home. (shrink)

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary (...) conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit. (shrink)

I argue for the causal character of modeling in data-intensive science, contrary to widespread claims that big data is only concerned with the search for correlations. After discussing the concept of data-intensive science and introducing two examples as illustration, several algorithms are examined. It is shown how they are able to identify causal relevance on the basis of eliminative induction and a related difference-making account of causation. I then situate data-intensive modeling within a broader framework of an epistemology of scientific (...) knowledge. In particular, it is shown to lack a pronounced hierarchical, nested structure. The significance of the transition to such “horizontal” modeling is underlined by the concurrent emergence of novel inductive methodology in statistics such as non-parametric statistics. Data-intensive modeling is well equipped to deal with various aspects of causal complexity arising especially in the higher level and applied sciences. (shrink)

Recent claims, mainly from computer scientists, concerning a largely automated and model-free data-intensive science have been countered by critical reactions from a number of philosophers of science. The debate suffers from a lack of detail in two respects, regarding the actual methods used in data-intensive science and the specific ways in which these methods presuppose theoretical assumptions. I examine two widely-used algorithms, classificatory trees and non-parametric regression, and argue that these are theory-laden in an external sense, regarding the framing of (...) research questions, but not in an internal sense concerning the causal structure of the examined phenomenon. With respect to the novelty of data-intensive science, I draw an analogy to exploratory as opposed to theory-directed experimentation. (shrink)

The success of particle detection in high energy physics colliders critically depends on the criteria for selecting a small number of interactions from an overwhelming number that occur in the detector. It also depends on the selection of the exact data to be analyzed and the techniques of analysis. The introduction of automation into the detection process has traded the direct involvement of the physicist at each stage of selection and analysis for the efficient handling of vast amounts of data. (...) This tradeoff, in combination with the organizational changes in laboratories of increasing size and complexity, has resulted in automated and semi-automated systems of detection. Various aspects of the semi-automated regime were greatly diminished in more generic automated systems, but turned out to be essential to a number of surprising discoveries of anomalous processes that led to theoretical breakthroughs, notably the establishment of the Standard Model of particle physics. The automated systems are much more efficient in confirming specific hypothesis in narrow energy domains than in performing broad exploratory searches. Thus, in the main, detection processes relying excessively on automation are more likely to miss potential anomalies and impede potential theoretical advances. I suggest that putting substantially more effort into the study of electron–positron colliders and increasing its funding could minimize the likelihood of missing potential anomalies, because detection in such an environment can be handled by the semi-automated regime—unlike detection in hadron colliders. Despite virtually unavoidable excessive reliance on automated detection in hadron colliders, their development has been deemed a priority because they can operate at currently highest energy levels. I suggest, however, that a focus on collisions at the highest achievable energy levels diverts funds from searches for potential anomalies overlooked due to tradeoffs at the previous energy thresholds. I also note that even in the same collision environment, different research strategies will opt for different tradeoffs and thus achieve different experimental outcomes. Finally, I briefly discuss current searches for anomalous process in the context of the previous analysis. (shrink)

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (shrink)

Along three measurements at the Large Hadron Collider (LHC), a high energy particle accelerator, we analyze procedures and consequences of exploratory experimentation (EE). While all of these measurements fulfill the requirements of EE: probing new parameter spaces, being void of a target theory and applying a broad range of experimental methods, we identify epistemic differences and suggest a classification of EE. We distinguish classes of EE according to their respective goals: the exploration where an established global theory cannot provide the (...) details of a local phenomenon, exploration of an astonishing discovery and exploration to find a new entity. We find that these classes also differ with respect to the existence of an identifiable target and their impact on the background theory. The characteristics distinguish EE from other kinds of experimentation, even though these different kinds have not yet been systematically studied. The formal rigor and precision of LHC physics facilitates to analyze concept formation in its early state. In particular we emphasize the importance for nil–results for conceptualization and argue that conceptualization can also be achieved from nil–results only. (shrink)

In the second half of the nineteenth century, gas discharge research was transformed from a playful and fragmented field into a new branch of physical science and technology. From the 1850s onwards, several technical innovations – powerful high-voltage supplies, the enhancement of glass-blowing skills, or the introduction of mercury air-pumps – allowed for a major extension of experimental practices and expansion of the phenomenological field. Gas discharge tubes served as containers in which resources from various disciplinary contexts could be brought (...) together; along with the experimental apparatus built around them the tubes developed into increasingly complex interfaces mediating between the human senses and the micro-world. The focus of the following paper will be on the physicist and chemist Johann Wilhelm Hittorf , his educational background and his attempts to understand gaseous conduction as a process of interaction between electrical energy and matter. Hittorf started a long-term project in gas discharge research in the early 1860s. In his research he tried to combine a morphological exploration of gas discharge phenomena – aiming at the experimental production of a coherent phenomenological manifold – with the definition and precise measurements of physical properties. (shrink)

In addition to his experiments on selection in pure lines, Wilhelm Johannsen performed less well-known hybridisation experiments with beans. This article describes these experiments and discusses Johannsen’s motivations and interpretations, in the context of developments in early genetics. I will show that Johannsen first presented the hybridisation experiments as an additional control for his selection experiments. The latter were dedicated to investigating heredity with respect to debates concerning the significance of natural selection of continuous variation for evolution. In the course (...) of the establishment of a Mendelian research program after 1900, the study of heredity gained increasing independence from questions of evolution, and focused more on the modes and mechanisms of heredity. Further to their role as control experiments, Johannsen also saw his hybridisation experiments as contributing to the Mendelian program, by extending the scope of the principles of Mendelian inheritance to quantitative characters. Towards the end of the first decade of genetics, Johannsen revisited his experiments to illustrate the many–many relationship between genes and characters, at a time when that relationship appeared increasingly complex, and the unit-character concept, accordingly, became inadequate. For the philosophy of science, the example shows that experiments can have multiple roles in a research programme, and can be interpreted in the light of questions other than those that motivated the experiments in the first place. (shrink)

In this essay, we examine the use of resting state fMRI data for psychological inferences. We argue that resting state studies hold the paired promises of discovering novel functional brain networks, and of avoiding some of the limitations of task-based fMRI. However, we argue that the very features of experimental design that enable resting state fMRI to support exploratory science also generate a novel confound. We argue that seemingly key features of resting state functional connectivity networks may be artefacts resulting (...) from sampling a ‘mixture distribution’ of diverse brain networks active at different times during the scan. We explore the consequences of this ‘mixture view’ for attempts to theorize about the cognitive or psychological functions of resting state networks, as well as the value of exploratory experiments. (shrink)

In this article, I introduce the notion of horizon for scientific practice (HSP), representing limits or boundaries within which scientists ply their trade, to facilitate analysis of scientific discovery and progress. The notion includes not only constraints that delimit scientific practice, e.g. of bringing experimentation to a temporary conclusion, but also possibilities that open up scientific practice to additional scientific discovery and to further scientific progress. Importantly, it represents scientific practice as a dynamic and developmental integration of activities to investigate (...) and analyze the natural world. I use the discovery of the clotting factor, thrombin, and the experiments conducted by the Johns Hopkins physiologist, William Howell, on the enzymatic nature of thrombin to illustrate the notion of HSP. In a concluding section, I compare the notion of HSP to other notions for scientific practice proposed in the history and philosophy of science literature. (shrink)

The purpose of this paper is to show how the degree of experimental validity of scientific procedures is crucially involved in determining two typical pragmatic modes in science, namely, the preservation of useful procedures and the disposal of useless ideas. The term 'pragmatic' will here be used following Schurz's characterisation of being internally pragmatic, as referring to that which proves useful for scientific or epistemic goals. The first part of the paper consists in a characterisation of the notion of experimental (...) validity. The second part is focused on several historical examples illustrating how the above pragmatic modes relate to the question of experimental validity. The Michelson-Morley experiment is presented as a case of a highly valid and useful experiment preserved through the development of different theories (like, on the one hand, the ether theory, upheld by Fitzgerald and Lorentz, and, on the other hand, Einstein's special theory of relativity). The concept of caloric will be discussed as an example of an idea that was discarded once it became useless, after heat was understood as a form of energy within the new frame provided by the kinetic theory of heat towards the middle of the 19th century. (shrink)

A notion of experimental series is developed, in which experiments or experimental sets are connected through experimental suggestions arising from previous experimental outcomes. To that end, the justification of Howard Temin’s DNA provirus hypothesis is examined. The hypothesis originated with evidence from two exploratory experimental sets on an oncogenic virus and was substantiated by including evidence from three additional experimental sets. Collectively these sets comprise an experimental series and the accumulative evidence from the series was adequate to justify the hypothesis (...) by persuading the virology community of its veracity. The notion of crucial experiment is also discussed in terms of experimental series. (shrink)

A notion of experimental series is developed, in which experiments or experimental sets are connected through experimental suggestions arising from previous experimental outcomes. To that end, the justification of Howard Temin's DNA provirus hypothesis is examined. The hypothesis originated with evidence from two exploratory experimental sets on an oncogenic virus and was substantiated by including evidence from three additional experimental sets. Collectively these sets comprise an experimental series and the accumulative evidence from the series was adequate to justify the hypothesis (...) by persuading the virology community of its veracity. The notion of crucial experiment is also discussed in terms of experimental series. (shrink)

Observation and experiment as categories for analysing scientific practice have a long pedigree in writings on science. There has, however, been little attempt to delineate observation and experiment with respect to analysing scientific practice; in particular, scientific experimentation, in a systematic manner. Someone who has presented a systematic account of observation and experiment as categories for analysing scientific experimentation is Ian Hacking. In this paper, I present a detailed analysis of Hacking’s observation versus experiment account. Using a range of cases (...) from various fields of scientific enquiry, I argue that the observation versus experiment account is not an adequate framework for delineating scientific experimentation in a systematic manner. (shrink)

According to Joshua Alexander, philosophers use intuitions routinely as a form of evidence to test philosophical theories but experimental philosophy demonstrates that these intuitions are unreliable and unrepresentative.1 According to Herman Cappelen, philosophers never use intuitions as evidence (despite the vacuous sentential leader ‘intuitively’) and experimental philosophy lacks a rationale for its much-touted existence.2 That two books are diametrically opposed on methodology in philosophy is not noteworthy. But eyebrows might be raised at such contradictory accounts of the phenomenology of philosophical (...) inquiry. What is it that (analytic) philosophers do? Why is it so difficult to achieve consensus on the professional activities in which we engage? (shrink)