We argue that the epistemic functions of replication in science are best understood by their role in assessing kinds of experimental error. Direct replications serve to assess the reliability of an experiment through its precision: the presence and degree of random error. Conceptual replications serve to assess the validity of an experiment through its accuracy: the presence and degree of systematic errors. To illustrate the aptness of this view, we examine the Hubble constant controversy in astronomy, showing how astronomers have (...) responded to the concordances and discordances in their results by carrying out the different kinds of replication that we identify, with the aim of establishing a precise, accurate value for the Hubble constant. We contrast our view with Machery’s “re-sampling” account of replicability, which maintains that replications only assess reliability. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

ABSTRACT It has long been held that the structure of a protein is determined solely by the interactions of the atoms in the sequence of amino acids of which it is composed, and thus the stable, biologically functional conformation should be predictable by ab initio or de novo methods. However, except for small proteins, ab initio predictions have not been successful. We explain why this is the case and argue that the relationship among the different methods, models, and representations of (...) protein structure is one of integrative pluralism. Our defence appeals to specific features of the complexity of the functional protein structure and to the partial character of representation in general. We present examples of integrative strategies in protein science. _1._ Introduction _2._ Partiality of Representation _3._ Protein Functional Complexity _4._ Modelling Protein Structure _4.1_ Integrating ab initio and experimental models _4.2_ Integrating multiple experimental models _5._ Conclusion. (shrink)

Summary We offer a novel historical-philosophical framework for discussing experimental practice which we call ‘Generating Experimental Knowledge’. It combines three different perspectives: experimental systems, concept formation, and the pivotal role of error. We then present an historical account of the invention of the Scanning Tunnelling Microscope (STM), or Raster-Tunnelmikroskop, and interpret it within the proposed framework. We show that at the outset of the STM project, Binnig and Rohrer—the inventors of the machine—filed two patent disclosures; the first is dated 22 (...) December 1978 (Switzerland), and the second, two years later, 12 September 1980 (US). By studying closely these patent disclosures, the attempts to realize them, and the subsequent development of the machine, we present, within the framework of generating experimental knowledge, a new account of the invention of the STM. While the realization of the STM was still a long way off, the patent disclosures served as blueprints, marking the changes that had to be introduced on the way from the initial idea to its realization. (shrink)

We propose that the epistemic functions of replication in science are best understood by relating them to kinds of experimental error/uncertainty. One kind of replication, which we call “direct replications,” principally serves to assess the reliability of an experiment through its precision: the presence and degree of random error/statistical uncertainty. The other kind of replication, which we call “conceptual replications,” principally serves to assess the validity of an experiment through its accuracy: the presence and degree of systematic errors/uncertainties. To illustrate (...) the aptness of this general view, we examine the Hubble constant controversy in astronomy, showing how astronomers have responded to the concordances and discordances in their results by carrying out the different kinds of replication that we identify, with the aim of establishing a precise, accurate value for the Hubble constant. We contrast our view with Machery's “re-sampling” account of replication, which maintains that replications only assess reliability. (shrink)

Abstract : A measurement result is never absolutely accurate: it is affected by an unknown “measurement error” which characterizes the discrepancy between the obtained value and the “true value” of the quantity intended to be measured. As a consequence, to be acceptable a measurement result cannot take the form of a unique numerical value, but has to be accompanied by an indication of its “measurement uncertainty”, which enunciates a state of doubt. What, though, is the value of measurement uncertainty? What (...) is its numerical value: how does one calculate it? What is its epistemic value: how one should interpret a measurement result? Firstly, we describe the statistical models that scientists make use of in contemporary metrology to perform an uncertainty analysis, and we show that the issue of the interpretation of probabilities is vigorously debated. This debate brings out epistemological issues about the nature and function of physical measurements, metrologists insisting in particular on the subjective aspect of measurement. Secondly, we examine the philosophical elaboration of metrologists in their technical works, where they criticize the use of the notion of “true value” of a physical quantity. We then challenge this elaboration and defend such a notion. The third part turns to a specific use of measurement uncertainty in order to address our thematic from the perspective of precision physics, considering the activity of the adjustments of physical constants. In the course of this activity, physicists have developed a dynamic conception of the accuracy of their measurement results, oriented towards a future progress of knowledge, and underlining the epistemic virtues of a never-ending process of identification and correction of measurement errors. (shrink)

This paper is concerned with the role of rational belief change theory in the philosophical understanding of experimental error. Today, philosophers seek insight about error in the investigation of specific experiments, rather than in general theories. Nevertheless, rational belief change theory adds to our understanding of just such cases: R. A. Fisher’s criticism of Mendel’s experiments being a case in point. After an historical introduction, the main part of this paper investigates Fisher’s paper from the point of view of rational (...) belief change theory: what changes of belief about Mendel’s experiment does Fisher go through and with what justification. It leads to surprising insights about what Fisher had done right and wrong, and, more generally, about the limits of statistical methods in detecting error. (shrink)

In this paper, we examine the history of the idea among physicists that there is a fundamental limit to physical measuring processes and that this limit is set by noise. In contrast to previous studies, that have focused on the realization of the existence of such a limit, we focus on the noise aspect of this history. In his monograph entitled Noise from 1954, the Dutch-American physicist and pioneer of noise Alder van der Ziel described how noise came to be (...) seen as of practical importance for measurements:The study of spontaneous fluctuations was primarily theoretical as recently as 1925. At that time it. (shrink)

The attempt to narrow the general discourse of the problem of error and to focus it on the specific problem of experimental error may be approached from different directions. One possibility is to establish a focusing process from the standpoint of history; such an approach requires a careful scrutiny of the history of science with a view to identifying the juncture when the problem of experimental error was properly understood and accounted for. In a study of this kind one would (...) have to examine the evolution of the method of experimentation and related topics so that clear criteria would underlie the analysis. (shrink)

If one follows the accounts by philosophers of science and the discussions in scientific communities, there can be little doubt that failure is an essential part of scientific practice. It is essential both in the sense of being integral to scientific practice and of being necessary for its overall success. Researchers who create new scientific knowledge face uncertainties about the nature of the problem they are trying to solve, the existence of a solution to that problem, the way in which (...) a solution can be found, and their ability to find such a solution (Gläser, 2007, 247). The existence of these uncertainties means, in turn, that each research process carries the risk of failure. (shrink)

A core, constitutive norm of science is to remove or remedy the artefacts in one’s data. Here, we consider examples of artefacts from many fields of science (for example, astronomy, economics, electrophysiology, psychology, and systems neuroscience) and discuss their contribution to a more general evidential selection problem at the heart of the epistemology of evidence. Synthesizing and building on previously disparate discussions in many areas of the philosophy of science, we provide a novel, causal–pragmatic account that fits the examples and (...) clarifies the practices by which artefacts are discovered and remedied. (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 (historical) accounts of scientific practice. (shrink)

It has long been held that the structure of a protein is determined solely by the interactions of the atoms in the sequence of amino acids of which it is composed, and thus the stable, biologically functional conformation should be predictable by ab initio or de novo methods. However, except for small proteins, ab initio predictions have not been successful. We explain why this is the case and argue that the relationship among the different methods, models, and representations of protein (...) structure is one of integrative pluralism. Our defence appeals to specific features of the complexity of the functional protein structure and to the partial character of representation in general. We present examples of integrative strategies in protein science. 1. Introduction2. Partiality of Representation3. Protein Functional Complexity4. Modelling Protein Structure4.1 Integrating ab initio and experimental models4.2 Integrating multiple experimental models5. Conclusion. (shrink)

Le projet à l’origine de ce dossier thématique est celui d’une étude comparative de l’expérimentation telle qu’elle apparaît dans les sciences de la nature et dans les sciences humaines et sociales. Il illustre et prolonge les réflexions d’un séminaire de recherche sur le même sujet, organisé par Catherine Allamel-Raffin, qui s’est tenu pendant deux ans (2017-2018) à l’université de Strasbourg grâce à un financement de la Misha (Maison Interuniversitaire des Sciences de l’Homme – Alsace). Les...

In this paper I explore an underdiscussed factor contributing to the replication crisis: Scientists, and following them policy makers, often neglect sources of errors in the production and interpretation of data and thus overestimate what can be learnt from them. This neglect leads scientists to conduct experiments that are insufficiently informative and science consumers, including other scientists, to put too much weight on experimental results. The former leads to fragile empirical literatures, the latter to surprise and disappointment when the fragility (...) of the empirical basis of some disciplines is revealed. (shrink)

This paper analyses the real origin and nature of scientific errors against claims of science critics, by examining a number of examples from the history of electricity and optics. This analysis leads to a conclusion that errors are a natural and unavoidable part of scientific process. If made available to students, through their science teachers, such a knowledge, would give students a deeper insight into the scientific process and remove their fear of making errors in their own laboratory work.

Le projet à l’origine de ce dossier thématique est celui d’une étude comparative de l’expérimentation telle qu’elle apparaît dans les sciences de la nature et dans les sciences humaines et sociales. Il illustre et prolonge les réflexions d’un séminaire de recherche sur le même sujet, organisé par Catherine Allamel-Raffin, qui s’est tenu pendant deux ans à l’université de Strasbourg grâce à un financement de la Misha. Les...

El recurso cognitivo por el cual la ciencia ha obtenido información del mundo empírico ha sido, desde su origen, la medición. Ésta está sujeta a un proceso continuo de regeneración y transformación histórica. Los principales análisis metateóricos que se han realizado sobre la medición son en su mayoría sobre sus aspectos formales. En este artículo desarrollo un bosquejo de un enfoque histórico y cognitivo de la medición científica con el fin de mostrar sus diversos aspectos cognitivos, metodológicos y epistemológicos, mismos (...) que han sido sistemáticamente descuidados por la gran mayoría de los análisis en filosofía de la ciencia. Measurement has been the main cognitive resource through which science has obtained empirical information about the world. Scientific measurement is not a fixed process but an historical and dynamical one; nevertheless, almost all philosophical analysis have studied it from a formal point of view. My aim in this paper is to outline a cognitive and historical notion of scientific measurement that allows us to appreciate its diverse epistemic, methodological, and cognitive features. (shrink)

: Errors in science range along a spectrum from those relatively local to the phenomenon (usually easily remedied in the laboratory) to those more conceptually derived (involving theory or cultural factors, sometimes quite long-term). One may classify error types broadly as material, observational, conceptual or discoursive. This framework bridges philosophical and sociological perspectives, offering a basis for interfield discourse. A repertoire of error types also supports error analytics, a program for deepening reliability through strategies for regulating and probing error.

The ArgumentWhile there has been muchattention given to experiment in modern science studies, there has been astoundingly little concern spared over the practice ofquanitataivemeasurment.Thus myths about the unreasonable effectiveness of mathematice in science still abound. This paper presents: An explicit mathematical model of the stabilization of quantitative constants in a mathematical science to rival older Bayesian and classical accounts;a framework for writing a history of pracitces with regard to treatment of quantitative measurement erroe; resourece for the comparative sociology of differing (...) discipliness in this regard;and a prolegonmena to a critique of orthodox economics and accounting theories. The key to all these diverse themes is the realization that no one individual alone is capable of fixing the magnitude of a quantitative error estimate, and therefore the social construction of error must be given a more precise meaning, an therefore the social construction of error must be given a more precise menaing, and that this occurs through the istrumentality of meta-analysis. (shrink)

: Peter Galison has recently claimed that twentieth-century microphysics has been pursued by two distinct experimental traditions--the image tradition and the logic tradition--that have only recently merged into a hybrid tradition. According to Galison, the two traditions employ fundamentally different forms of experimental argument, with the logic tradition using statistical arguments, while the image tradition strives for non-statistical demonstrations based on compelling ("golden") single events. I show that discoveries in both traditions have employed the same statistical form of argument, even (...) when basing discovery claims on single, golden events. Where Galison sees an epistemic divide between two communities that can only be bridged by a creole- or pidgin-like "interlanguage," there is in fact a shared commitment to a statistical form of experimental argument. (shrink)

This essay is concerned with the epistemic roles of error in scientific practice. Usually, error is regarded as something negative, as an impediment or obstacle for the advancement of science. However, we also frequently say that we are learning from error. This common expression suggests that the role of error is not—at least not always—negative but that errors can make a fruitful contribution to the scientific enterprise. My paper explores the latter possibility. Can errors play an epistemically productive role in (...) scientific research? The paper begins with a review of several twentieth-century approaches to error and the various agendas behind them. It is shown that only very few scholars have considered whether errors can be productive. The main part of the paper examines a concrete debate in early nineteenth-century microscopy and analyses how the microscopists coped with the problem of error. Drawing on this material, the article offers some terminological clarifications of the common notion ‘learning from error’. The conclusion argues that error can indeed play epistemically productive roles in scientific practice.Keywords: Error; Nineteenth-century microscopic anatomy. (shrink)

SUMMARYBy examining the use of tissue culture in post-war American biomedicine, this paper investigates how scientists experience and manage failure. I study how Leonard Hayflick forged his new definition of failure and ways of managing it by refuting Alexis Carrel's definition of failure alongside his theory of the immortality of cultured cells. Unlike Carrel, Hayflick claimed that every vertebrate somatic cell should eventually die, unless it transformed into a tumour cell. This claim defined cell death, which had been a problem (...) leading to a laboratory failure, as a normal phenomenon. On the other hand, permanent life, which had been considered a normal cellular characteristic, became a major factor causing scientific failure, since it implied malignant transformation that scientists hoped to control. Hayflick then asserted that his cell strains and method would partly enable scientists to manage this factor—especially that occurred through viral infection—alongside other causes of failure in routine tasks, including bacterial contamination. I argue that the growing biomedical enterprise fostered this work of Hayflick's, which had repercussions in both his career and the uses of cells in diverse investigations. His redefinition of failure in the age of biomedicine resulted in the broad dissemination of his cells, medium, and method as well as his long struggle with the National Institutes of Health, which caused his temporarily failed career. (shrink)

Recent breakthroughs in the history and sociology of science have begun to help us to appreciate the vast complexity and intricate character of empirical endeavours in the sciences. The days when philosophers could blandly gesture towards “observation statements” or “falsification,” as if they were some readily understood phenomena or set of procedures, are gone, happily. This does not mean we can merely use the Duhem-Quine thesis as a shibboleth, however: we are now much more sensitive to immense difficulties in establishing (...) viable claims to replication or establishing the absence of selectivity bias, or convincing others of adequacy of experimental controls. Yet, even so, I would still assert that modern science studies, with only a very few exceptions, have ignored the problem of the constitution of error in the context of precision quantitative measurement. While rather broad claims have been made concerning measurement by Hacking, Cartwright, Franklin and others, none goes so far as to examine the actual manipulation of the numerical data. More distressingly, in the areas of economics and economic methodology, we have not even got so far as have the researchers in science studies. This fact alone should provide grounds for scepticism about the claim in Cartwright that philosophy of scientific inference has something to learn from the history of econometrics. (shrink)

According to the demand of the Hypothetico-Deductive (H-D) method, a theory is confirmed when the prediction-observation (p-o) gap is small and disconfirmed when the gap is large. A major goal of this paper is to introduce a research domain for which this demand does not hold. In contrast to the H-D method's demand, this research, called the Catch model for reconstructing a face previously seen from memory, requires an increase, within limits, in the p-o gap. The Catch model research substantiates (...) theoretically and empirically a new proposed method that I call the "Deductive-Reconstruction" (D-R) method. This method provides essential conditions whose fulfillment guarantees successful reconstruction of past events (a face previously seen) from memory. It is argued that the D-R method fits the area of research of reconstructing past events from memory better than the H-D method. Application of the H-D method to the Catch model's research domain leads to an internal contradiction and failure to reconstruct past events (a face previously seen) from memory. Finally, the nature of the D-R method along with the Catch model is discussed from three points of view: confirmation, explanation, and generality. (shrink)