Experimentation in Science

In the first part of this paper, I will sketch the main features of traditional models of evidence, indicating idealizations in such models that I regard as doing more harm than good. I will then proceed to elaborate on an alternative model of evidence that is functionalist, complex, dynamic, and contextual, which I will call DYNAMIC EVIDENTIAL FUNCTIONALISM. I will demonstrate its application to an illuminating example of scientific inquiry, and defend it from some likely objections. In the second part, (...) I will use that alternative to solve a variety of classic and contemporary problems in the literature on scientific evidence having to do with the empirical basis of science and the use of evidence in public policy. (shrink)

I argue that Binkley et al. use causal process tracing in conjunction with a natural trajectory experiment and two natural snapshot experiments in their re-examination of the Kaibab. This shows that Aldo Leopold may have been right about trophic cascade in the Kaibab in the 1920s, i.e., that there are good reasons to think that a loss of predators led to a deer irruption which decreased aspen recruitment. Using the different cause-finding practices in combination can strengthen causal inferences and mitigate (...) the shortcomings that each practice has. (shrink)

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation (in astrophysics, ecology, economics, climatology, etc.). But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim (...) that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)

I praise Franklin's full descriptions of important and exemplary experiments, and wish that he had said more about why they are exemplary.

Computer simulations are nowadays often directly involved in the generation of experimental results. Given this dependency of experiments on computer simulations, that of simulations on models, and that of the models on free parameters, how do researchers establish trust in their experimental results? Using high-energy physics (HEP) as a case study, I will identify three different types of robustness that I call conceptual, methodological, and parametric robustness, and show how they can sanction this trust. However, as I will also show, (...) simulation models in HEP themselves fail to exhibit a type of robustness I call inverse parametric robustness. This combination of robustness and failures thereof is best understood by distinguishing different epistemic capacities of simulations and different senses of trust: Trusting simulations in their capacity to facilitate credible experimental results can mean accepting them as means for generating belief in these results, while this need not imply believing the models themselves in their capacity to represent an underlying reality. (shrink)

Despite the conceptual problems in identifying the placebo effect, an increasing number of multidisciplinary inquiries rest on the assumption that there is a distinct class of effects, placebo effects. In this chapter, I argue against this assumption. I present cases and characterizations of the placebo effect as offered in the literature, and argue that the latter are subject to insurmountable problems. Moreover, I argue that identification of placebo effects as such is not useful for the three main purposes offered in (...) the literature. I then offer suggestions for why it may remain intuitive that some effects are placebo effects and close by noting the potential benefits of ultimately explaining away these intuitions. (shrink)

It is often claimed that only experiments can support strong causal inferences and therefore they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments results in their overuse both by researchers and decision-makers, and in an underappreciation of their shortcomings. Neglecting other methods often follows. Experiments can suggest whether X causes Y in a specific experimental setting; however, they often fail to elucidate either the mechanisms responsible for an effect, or the strength of an effect in everyday natural (...) settings. In this paper, we consider two overarching issues. First, experiments have important limitations. We highlight problems with: external, construct, statistical conclusion, and internal validity; replicability; and with conceptual issues associated with simple X-causes-Y thinking. Second, quasi-experimental and non-experimental methods are absolutely essential. As well as themselves estimating causal effects, these other methods can provide information and understanding that goes beyond that provided by experiments. A research program progresses best when experiments are not treated as privileged but instead are combined with these other methods. (shrink)

I examine the (mediated) correspondence between Spinoza and Robert Boyle concerning the latter’s account of fluidity and his experiments on reconstitution of niter in the light of the epistemology and doctrine of method contained in the Treatise on the Emendation of the Intellect. I argue that both the Treatise and the correspondence reveal that for Spinoza, the proper method of science is not experimental, and that he accepted a powerful under-determination thesis. I argue that, in contrast to modern versions, Spinoza’s (...) form of naturalism was a highly rationalist and anti-empirical one. I conclude with a brief account of the value of experience and experimentation for Spinoza’s scientific method. (shrink)

It has been argued that supervenience generates unavoidable confounding problems for interventionist accounts of causation, to the point that we must choose between interventionism and supervenience. According to one solution, the dilemma can be defused by excluding non-causal determinants of an outcome as potential confounders. I argue that this solution undermines the methodological validity of causal tests. Moreover, we don’t have to choose between interventionism and supervenience in the first place. Some confounding problems are effectively circumvented by experimental designs routinely (...) employed in science. The remaining confounding issues concern the physical interpretation of variables and cannot be solved by choosing between interventionism and supervenience. (shrink)

"Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely correlational (...) data contains information that allows us to draw causal inferences: statistical noise. Methods for extracting causal knowledge from noise provide us with an alternative to randomized controlled trials that allows us to reach causal conclusions from purely correlational data. (shrink)

Abstraction and generalization are two processes of reasoning that have a special role in the construction of scientific theories and models. They have been important parts of the scientific method ever since the nineteenth century. A philosophical and historical analysis of scientific practices shows how abstraction and generalization found their way into the theory of the logic of science of the nineteenth-century philosopher Charles S. Peirce. Our case studies include the scientific practices of Francis Galton and John Herschel, who introduced (...) composite photographs and graphical methods, respectively, as technologies of generalization and thereby influenced Peirce’s logic of abstraction. Herschel’s account of generalization is further supported by William Whewell, who was very influential on Peirce. By connecting Herschel’s scientific technology of abstraction to Peirce’s logical technology of abstraction—namely, diagrams—we highlight the role of judgments in scientific observation by hypostatic abstractions. We also relate Herschel’s discovery-driven logic of science and Peirce’s open-ended diagrammatic logic to the use of models in science. Ultimately, Peirce’s theory of abstraction is a case of showing how logic applies to reality. (shrink)

In 1981, David Hubel and Torsten Wiesel received the Nobel Prize for their research on cortical columns—vertical bands of neurons with similar functional properties. This success led to the view that “cortical column” refers to the basic building block of the mammalian neocortex. Since the 1990s, however, critics questioned this building block picture of “cortical column” and debated whether this concept is useless and should be replaced with successor concepts. This paper inquires which experimental results after 1981 challenged the building (...) block picture and whether these challenges warrant the elimination “cortical column” from neuroscientific discourse. I argue that the proliferation of experimental techniques led to a patchwork of locally adapted uses of the column concept. Each use refers to a different kind of cortical structure, rather than a neocortical building block. Once we acknowledge this diverse-kinds picture of “cortical column”, the elimination of column concept becomes unnecessary. Rather, I suggest that “cortical column” has reached conceptual retirement: although it cannot be used to identify a neocortical building block, column research is still useful as a guide and cautionary tale for ongoing research. At the same time, neuroscientists should search for alternative concepts when studying the functional architecture of the neocortex. keywords: Cortical column, conceptual development, history of neuroscience, patchwork, eliminativism, conceptual retirement. (shrink)

William Gilbert’s 1600 book, De magnete, greatly influenced early modern natural philosophy. The book describes an impressive array of physical experiments, but it also advances a metaphysical view at odds with the soon to emerge mechanical philosophy. That view was animism. I distinguish two kinds of animism – Aristotelian and Platonic – and argue that Gilbert was an Aristotelian animist. Taking Robert Boyle as an example, I then show that early modern arguments against animism were often effective only against Platonic (...) animism. In fact, unacknowledged traces of Aristotelian animism can be found in Boyle’s mechanical account of nature. This was Gilbert’s legacy. (shrink)

Ce livre est un livre d’épistémologie de la sociologie. L’objectif est d’appliquer des méthodes analytiques pour clarifier le vocabulaire, expliciter des relations non-apparentes entre concepts, dégager la portée d’une méthode, ou souligner les incohérences d’un programme de recherche. Les questions épineuses ne sont pas écartéees: Comment clarifier des notions confuses? Peut-on mathématiser les concepts sociologiques? Peut-on pratiquer la sociologie comme on pratique les sciences naturelles? Quelle est la place du déterminisme? Chaque question est examinée à la fois dans sa structure (...) logique et sur des cas concrets. La mathématisation est étudiée sur les mécanismes agrégatifs et sur les modèles de diffusion des innovations. La sociologie expérimentale – généralement méconnue dans la sociologie française – est étudiée sur des programmes de relogement, la diffusion de l’information, ou la genèse de la solidarité sociale. Le livre aborde frontalement la question du déterminisme, du naturalisme, du matérialisme et du scientisme, réputés intenables en sociologie. L’enquête montre que leur rejet résulte généralement de confusions conceptuelles. Une fois écartées, peu d’obstacles s’opposent à leur emploi en sociologie. L’objet de ce livre est la sociologie fondamentale: ensemble des mécanismes qui structurent la production des connaissances sociologiques de base à partir de concepts, programmes ou principes, c’est-à-dire tout ce qui ne relève pas de l’expérience immédiate du terrain et des mondes sociaux. (shrink)

This book proposes a novel position in the debate on scientific realism: Modal Empiricism. Modal empiricism is the view that the aim of science is to provide theories that correctly delimit, in a unified way, the range of experiences that are naturally possible given our position in the world. The view is associated with a pragmatic account of scientific representation and an original notion of situated modalities, together with an inductive epistemology for modalities. It purports to provide a faithful account (...) of scientific practice and of its impressive achievements, and defuses the main motivations for scientific realism. More generally, Modal Empiricism purports to be the precise articulation of a pragmatist stance towards science. This book is of interest to any philosopher involved in the debate on scientific realism, or interested in how to properly understand the content, aim and achievements of science. (shrink)

Ian Hacking’s Representing and Intervening is often credited as being one of the first works to focus on the role of experimentation in philosophy of science, catalyzing a movement which is sometimes called the “philosophy of experiment” or “new experimentalism”. In the 1980s, a number of other movements and scholars also began focusing on the role of experimentation and instruments in science. Philosophical study of experimentation has thus seemed to be an invention of the 1980s whose central figure is Hacking. (...) This article aims to assess this historical claim, made by Hacking himself as well as others. It does so first by highlighting how a broader perspective on the history of philosophy reveals this invention narrative to be incorrect, since experimentation was a topic of interest for earlier philosophers. Secondly, the article evaluates a revision of this historical claim also made by some philosophers of experiment: the rediscovery narrative, which frames Hacking and others as having rediscovered the work of these earlier authors. This second narratives faces problems as well. Therefore we develop a third narrative which we call the contextualist narrative. Rather than considering experimentation in an essentialist manner as a fixed research object that is either present or not in the work of specific authors, experimentation should be addressed through a narrative that asks in what way it becomes a philosophical problem for certain authors and for what purpose. Such contextualization enables a repositioning of Hacking’s philosophy of experiment in relation to the specific debates in which he intervened, such as the realism-antirealism debate, the Science Wars and the debate on incommensurability. (shrink)

Ian Hacking instigated a revolution in 20th century philosophy of science by putting experiments (“interventions”) at the top of a philosophical agenda that historically had focused nearly exclusively on representations (“theories”). In this paper, I focus on a set of conceptual tools Hacking (1992) put forward to understand how laboratory sciences become stable and to explain what such stability meant for the prospects of unity of science and kind discovery in experimental science. I first use Hacking’s tools to understand sources (...) of instability and disunity in rodent behavioral neuroscience. I then use them to understand recent grass-roots collaborative open science initiatives aimed at establishing stability in this research area and tease out some implications for unity of science and kind creation and discovery in cognitive neuroscience. -/- . (shrink)

This paper explores the experiments of the English mathematician Thomas Harriot on specific gravity in the years 1600-1605, as recorded in a series of manuscript notes in British Library Add. MS 6788. It examines the programme of reading undertaken by Harriot before these experiments, and describes a series of experiments conducted by him which compared the weight of a wide variety of substances in air and water. Harriot’s work is compared to that of his contemporary Marino Ghetaldi in Promotus Archimedis, (...) and the work of both mathematicians can be positioned in the context of sixteenth-century mathematical responses to the famous problem posed by Hiero, King of Syracuse to Archimedes. Harriot’s use of proportional mathematics in his experimental work and his application of this technique to problems in the alloying of metal and chymical analysis is examined in detail. (shrink)

The French physicist Jean Baptiste Perrin is widely credited with providing the conclusive argument for atomism. The most well-known part of Perrin’s argument is his description of thirteen different procedures for determining Avogadro’s number (N)–the number of atoms, ions, and molecules contained in a gram-atom, gram-ion, and gram-mole of a substance, respectively. Because of its success in ending the atomism debates Perrin’s argument has been the focus of much philosophical interest. The various philosophers, however, have reached different conclusions, not only (...) about the argument’s general rationale but also the role that the multiple determination of N played in it. This paper emphasizes the historical development of Perrin’s experimental work in order to understand the role that the multiple determination of molecular magnitudes played in his argument for molecular reality. It claims that Perrin used the multiple determination strategy to put forward an exceptionally strong no-coincidence argument to argue for both the correctness of the values for the molecular magnitudes determined and the validity of the auxiliary assumptions upon which the different determinations were based. The historicist approach also allows the identification of the elements responsible for the epistemic strength of Perrin’s no-coincidence argument. (shrink)

Multiple determination is the epistemic strategy of establishing the same result by means of multiple, independent procedures. It is an important strategy praised by both philosophers of science and practicing scientists. Despite the heavy appeal to multiple determination, little analysis has been provided regarding the specific grounds upon which its epistemic virtues rest. This article distinguishes between the various dimensions of multiple determination and shows how they can be used to evaluate the epistemic force of the strategy in particular cases. (...) Distinguishing between the various dimensions helps to resolve the disagreements regarding the relevance and epistemic import of multiple determination for scientific research. It also suggests a fruitful mode of interaction between the philosophy of science and accounts of scientific practice. (shrink)

Conducting research on animals is supposed to be valuable because it provides information on how human mechanisms work. But for the use of animal models to be ethically justified, it must be epistemically justified. The inference from an observation about an animal model to a conclusion about humans must be warranted for the use of animals to be moral. When researchers infer from animals to humans, it’s an extrapolation. Often non-human primates are used as animal models in laboratory behavioral research. (...) The target populations are humans and other non-human primates. I argue that the epistemology of extrapolation renders the use of non-human primates in laboratory behavioral research unreliable. If the model is relevantly similar to the target, then the experimental conditions introduce confounding variables. If the model is not relevantly similar to the target, then the observations of the model cannot be extrapolated to the target. Since using non-human primates in as animal models in laboratory behavioral research is not epistemically justified, using them as animal models in laboratory behavioral research is not ethically justified. (shrink)

The Historia densi et rari, published posthumously in 1658, is probably Francis Bacon’s most complex natural and experimental history. It contains observations and experimental reports, quantitative estimates and tables, and theoretical and methodological considerations, in a structure which has never been fully investigated. I provide here a fresh reading of this text from the perspective of scientific practices. I claim that Historia densi et rari represents a quantitative and instrumental investigation assembled with the help of Bacon’s philosophy of experiment as (...) developed in the Novum organum. I first discuss the role played in the Historia densi et rari by the various instances of special power in delineating the object of research. I then analyze the ways in which a special class of instances of special power, the “mathematical instances,” are used in the Historia densi et rari to make the inquiry both more precise, and more abstract. Bacon used mathematical instances to transform traditional recipes of pneumatics into quantitative, more general investigations into universal motions and processes. Finally, I discuss two examples of scientific practice at work: the attempt to use instruments to gradually define and clarify “proper” notions of “rarefaction” and “condensation,” and the redefinition of a metaphysical concept in instrumental and operational terms. (shrink)

This discussion centers on two desiderata: the role of measurement in information-gathering and physical interaction in scientific practice. By taking inspiration from van Fraassen’s view, we present a methodological account of perspectival measurement that addresses empirical practice where there is complex intervention, disagreeing results, and limited theory. The specific aim of our account is to provide a methodological prescription for developing measurement processes in the context of limited theory. The account should be useful to philosophers of science, who are interested (...) in the intersection between representation and intervention; scientists, who are interested in methodological suggestions for theory-development and reliability; and interdisciplinary researchers, who are interested in the intersections between the pandemic, built environments, and social processes. We apply the process-view of measurement to COVID-19, specifically, measuring replication in the SARS-CoV-2 virus. The aim is to show that our account tracks key elements—manipulation/intervention, independence, invariance, and theory-development—by organizing unfolding measurement processes. Additionally, we use our account to make prescriptive suggestions for measurement practice in the COVID-19 context by discussing the need to broaden measurement perspective on interaction, manipulation, and production. (shrink)

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

This paper explores how a set of observations on the weight of lead were interpreted and assessed between the 1540s and the 1630s across three different interconnecting disciplines: medicine, mineralogy and chemistry. The epistemic import of these discussions will be demonstrated by showing: 1) the changing role and articulation of experience and quantification in the investigation of metals; and 2) the notions associated with weight in different disciplinary frameworks. In medicine and mineralogy, weight was not considered as a specific subject (...) of inquiry in itself, but as a “sign” indicating other relevant properties of metals. In contrast, the chemistry tradition was increasingly concerned with the specific investigation of weight as a property of matter, as seen in the debates that took place in the “chemical revolution.” In addition, this study will reveal the versatility, polysemy, and parallel purposes of the recourse to experiential knowledge in different contexts, where the same “facts” operate within different disciplines. (shrink)

Numerous early modern experimentalists, including Galileo Galilei, Francis Bacon and Thomas Harriot, viewed one seemingly humble principle – that at a given volume, different substances can be identified by their particular weight, or specific gravity – as a fundamental key to the understanding of nature in general. Johannes Kepler’s Messekunst Archimedis of 1616 contains a striking summary of the experimental research on specific gravities in the long sixteenth-century. Counting himself amongst an extensive list of authors interested in this problem, Kepler (...) mentions not only natural philosophers or mathematicians interested in Archimedes. His account surprisingly includes humanists, instrument makers, antiquarians and assayers. Received histories of specific gravities often focus on antecedents of modern disciplinary concepts and methodologies, where instead, Kepler’s account suggests the existence of a heterogeneous group of early modern experts involved in experiments on the quantification of matter, at the intersection between the history of science, practical mathematics and the humanities. (shrink)

The multiple detections of gravitational waves by LIGO (the Laser Interferometer Gravitational-Wave Observatory), operated by Caltech and MIT, have been acclaimed as confirming Einstein's prediction, a century ago, that gravitational waves propagating as ripples in spacetime would be detected. Yunes and Pretorius (2009) investigate whether LIGO's template-based searches encode fundamental assumptions, especially the assumption that the background theory of general relativity is an accurate description of the phenomena detected in the search. They construct the parametrized post-Einsteinian (ppE) framework in response, (...) which broadens those assumptions and allows for wider testing under more flexible assumptions. Their methods are consistent with work on confirmation and testing found in Carnap (1936), Hempel (1969), and Stein (1992, 1994), with the following principles in common: that confirmation is distinct from testing, and that, counterintuitively, revising a theory's formal basis can make it more broadly empirically testable. These views encourage a method according to which theories can be made abstract, to define families of general structures for the purpose of testing. With the development of the ppE framework and related approaches, multi-messenger astronomy is a catalyst for deep reasoning about the limits and potential of the theoretical framework of general relativity. (shrink)

The enduring replication crisis in many scientific disciplines casts doubt on the ability of science to estimate effect sizes accurately, and in a wider sense, to self-correct its findings and to produce reliable knowledge. We investigate the merits of a particular countermeasure—replacing null hypothesis significance testing with Bayesian inference—in the context of the meta-analytic aggregation of effect sizes. In particular, we elaborate on the advantages of this Bayesian reform proposal under conditions of publication bias and other methodological imperfections that are (...) typical of experimental research in the behavioral sciences. Moving to Bayesian statistics would not solve the replication crisis single-handedly. However, the move would eliminate important sources of effect size overestimation for the conditions we study. (shrink)

In 1955, Norbert Wiener suggested a sociological model according to which all forms of culture ultimately depended on the temporal coordination of human activities, in particular their synchronization. The basis for Wiener’s model was provided by his insights into the temporal structures of cerebral processes. This article reconstructs the historical context of Wiener’s ‘brain clock’ hypothesis, largely via his dialogues with John W. Stroud and other scholars working at the intersection of neurophysiology, experimental psychology, and electrical engineering. Since the 19th (...) century, physiologists and psychologists have been conducting experimental investigations into the relation between time and the brain. Using innovative instruments and technologies, Stroud rehearsed these experiments, in part without paying any attention at all to the experimental traditions involved. Against this background, this article argues that the novelty of Wiener’s model relies largely on his productive rephrasing of physiological and psychological findings that had been established long before the Second World War. (shrink)

Examining tensions between the past and present uses of scientific concepts can help clarify their contributions as tools in experimental practices. This point can be illustrated by considering the concepts of mental imagery and hallucinations: despite debates over their respective referential reliabilities remaining unresolved within their interdependent histories, both are used as independently stable concepts in neuroimaging experiments. Building on an account of how these concepts function as tools structured for pursuit of diverging goals in experiments, this paper explores this (...) tension by re-examining the continued reliance of each concept on inverse characterisations inherited from the nominally-discarded ‘mediator-view’ of sensory-like mental phenomena (SLMP). In doing so, I seek to demonstrate how examining unresolved tensions can help highlight that entrenched associations can remain both integral to, and obscured by, the uses of concepts as goal-directed tools within experimental practices. (shrink)

Neutral Theory is controversial in ecology. Ecologists and philosophers have diagnosed the source of the controversy as: its false assumption that individuals in different species within the same trophic level are ecologically equivalent, its conflict with Competition Theory and the adaptation of species, its role as a null hypothesis, and as a Lakatosian research programme. In this paper, I show why we should instead understand the conflict at the level of research programs which involve more than theory. The Neutralist and (...) Competitionist research programs borrow and construct theories, models, and experiments for various aims and given their home ecological systems. I present a holistic and pragmatic view of the controversy that foregrounds the interrelation between many kinds of practices and decisions in ecological research. (shrink)

Many questions about the fundamentals of some area take the form “What is …?” It does not come as a surprise then that, at the dawn of Western philosophy, Socrates asked the questions of what piety, courage, and justice are. Nor is it a wonder that the philosophical preoccupation with computer simulations centered, among other things, about the question of what computer simulations are. Very often, this question has been answered by stating that computer simulation is a species of a (...) well-known method, e.g., experimentation. Other answers claim at least a close relationship between computer simulation and another method. In any case, correct answers to the question of what a computer simulation is should help us to better understand what validation of simulations is. The aim of this chapter is to discuss the most important proposals to understand computer simulation in terms of another method and to trace consequences for validation. Although it has sometimes been claimed that computer simulations are experiments, there are strong reasons to reject this view. A more appropriate proposal is to say that computer simulations often model experiments. This implies that the simulation scientists should to some extent imitate the validation of an experiment. But the validation of computer simulations turns out to be more comprehensive. Computer simulations have also been conceptualized as thought experimentsThought experiment or close cousins of the latter. This seems true, but not very telling since thought experiments are not a standardStandard method and since it is controversial how they contribute to our acquisition of knowledge. I thus consider a specific view on thought experiments to make some progress on understanding simulations and their validation. There is finally a close connection between computer simulation and modeling, and it can be shown that the validation of a computer simulation is the validation of a specific model, which may either be thought to be mathematical or fictional. (shrink)

Traditionally, in the literature on robustness analysis objects are classified as genuine phenomena (natural objects, events, and processes) or artifacts (results produced in error). But much of biological measurement requires the manipulation of local experimental conditions in order to produce new effects. These types of intervention-based regularities are neither natural objects nor artifacts; characterizing them as either fails adequately to address key ontological properties as well as their role in scientific practice. It is argued that a new classification, based on (...) methodological considerations, can be useful in order to characterize experimental productions. Experimentally-useful context-sensitive objects are referred to as ‘artefacts’. To show how the new classification works and why it is instructive for scientific practice, two case studies are discussed. First, the puzzle of arsenic-consuming living organisms is analyzed, where under a set of specific experimental conditions a given organism was found to replace phosphorous with arsenic in its DNA. Second, ecological epigenetic measurement is discussed to show the complexity of variant effects in the context of lab, field, and computer measurements. It is argued that the line between artifacts and artefacts is fluid because theoretical, experimental, and practical considerations vary. (shrink)

In a well-cited book chapter, ecologist Jared Diamond characterizes three main types of experiment performed in community ecology: laboratory experiment, field experiment, and natural experiment. Diamond argues that each form of experiment has strengths and weaknesses, with respect to, for example, realism or the ability to follow a causal trajectory. But does Diamond’s typology exhaust the available kinds of cause-finding practices? Some social scientists have characterized something they call “causal process tracing.” Is this a fourth type of experiment or something (...) else? I examine Diamond’s typology and causal process tracing in the context of a case study concerning the dynamics of wolf and deer populations on the Kaibab Plateau in the 1920s, a case that has been used as a canonical example of a trophic cascade by ecologists but which has also been subject to controversy. I argue that ecologists have profitably deployed causal process tracing together with other types of experiment to help settle questions of causality in this case. It remains to be seen how widespread the use of causal process tracing outside of the social sciences is (or could be), but there are some potentially promising applications, particularly with respect to questions about specific causal sequences. (shrink)

The applications of machine learning and deep learning to the natural sciences has fostered the idea that the automated nature of algorithmic analysis will gradually dispense human beings from scientific work. In this paper, I will show that this view is problematic, at least when ML is applied to biology. In particular, I will claim that ML is not independent of human beings and cannot form the basis of automated science. Computer scientists conceive their work as being a case of (...) Aristotle’s poiesis perfected by techne, which can be reduced to a number of straightforward rules and technical knowledge. I will show a number of concrete cases where at each level of computational analysis, more is required to ML than just poiesis and techne, and that the work of ML practitioners in biology needs also the cultivation of something analogous to phronesis, which cannot be automated. But even if we knew how to frame phronesis into rules, still this virtue is deeply entrenched in our biological constitution, which computers lack. Whether computers can fully perform scientific practice independently of humans is an ill-posed question. (shrink)

Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I (...) discuss precedents and evidence for the crisis. Second, I discuss methodological, statistical, and social-structural factors that have contributed to the crisis. Third, I focus on the philosophical issues raised by the crisis. Finally, I discuss proposed solutions and highlight the gaps that philosophers could focus on. (shrink)

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents data-driven approaches in social epistemology (...) of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

The Greenough stereomicroscope, or “Stemi” as it is colloquially known among microscopists, is a stereoscopic binocular instrument yielding three-dimensional depth perception when working with larger microscopic specimens. It has become ubiquitous in laboratory practice since its introduction by the unknown scientist Horatio Saltonstall Greenough in 1892. However, because it enabled new experimental practices rather than new knowledge, it has largely eluded historical and epistemological investigation, even though its design, production, and reception in the scientific community was inextricably connected to the (...) new epistemological ideals of the life sciences caught between natural history and modern science. The development of the microscope will be contextualized within the scientific and technological landscape, showing how Greenough navigated his way through this terrain, and what led him to sow the seeds for the stereoscopic microscope. The historical controversy over the optical mechanism, through which the instrument would generate the desired depth perception, and how this quality was embedded into laboratory practice, will be examined. Subsequently, it will become evident that the specific image of nature produced by the stereoscopic microscope corresponded to the new ideals of the life sciences and their representation. (shrink)