Funding policies for science are usually directed at supporting technological innovations. The im-pact and success of such policies depend crucially on how science and technology are connected to each other. I propose an “interactive view” of the relationship between basic science and technol-ogy development which comprises the following four claims: First, technological change derives from science but only in part. The local models used in accounting for technologically relevant phenomena contain theoretical and non-theoretical elements alike. Second, existing technologies and rules (...) of experience constitute another major repository of technological inventions. Third, technology dynamics is only weakly coupled to progress in basic science but it is closely related to science. There is a dependence of technological change on a more fundamental understanding, to be sure, but it is of an indirect and long-term character. Fourth, progress in basic research is some-times the effect (rather than the cause) of technological change. Technological change sometimes brings about increased theoretical understanding (application innovation). (shrink)

Application in science has its own structure, distinct from the structure of theoretical science, and therefore needs its own philosophy. The covering power of a formal scientific theory is no guide to its explanatory power. Explanation is too much to ask of a fundamental scientific theory. This is seen by considering two strands of the Born-Einstein debate: first the explanatory power of quantum mechanics and second, the reality of unobserved properties. The function of theoretical physics is to describe rather than (...) to explain. Some techniques are a standard part of theory; while some aread hoc to the problems at hand. Very few of the derivations in mathematical physics are explanatory. This shows distinctly separate structures for theory and for application. (shrink)

Editorial introduction to special issue on 'Model-based representation in scientific practice'.

The problem for the scientist created by using idealizations is to determine whether failures to achieve experimental fit are attributable to experimental error, falsity of theory, or of idealization. Even in the rare case when experimental fit within experimental error is achieved, the scientist must determine whether this is so because of a true theory and fortuitously canceling idealizations, or due to a fortuitous combination of false theory and false idealizations. For the engineer, the problem seems rather different. Experiment for (...) the engineer reveals the closeness of predictive fit that can be achieved by theory and idealization for a particular case. If the closeness of fit is good enough for some practical purpose, the job is done. If not, or there are reasons to consider variation, then the engineer needs to know how well the experimentally determined closeness of fit will extrapolate to new cases. This paper focuses on engineering measures of closeness of fit and the projectibility of those measures to new cases. (shrink)

In the literature on scientific practices, one finds sustained analyses of the contextualist elements of inquiry. However, the ways in which local and disciplinary contexts of practice function as common goods remain largely unexplored. In this paper I argue that a contextualist analysis of scientific practices as common goods can shed light on the challenges of scientific communication and interdisciplinary collaboration, albeit without invoking Kuhn's problematic notion of incommensurability.

Robertson's earlier work, The New Renaissance projected the likely future impact of computers in changing our culture. Phase Change builds on and deepens his assessment of the role of the computer as a tool driving profound change by examining the role of computers in changing the face of the sciences and mathematics. He shows that paradigm shifts in understanding in science have generally been triggered by the availability of new tools, allowing the investigator a new way of seeing into questions (...) that had not earlier been amenable to scientific probing. (shrink)

Popper repeatedly emphasised the significance of a critical attitude, and a related critical method, for scientists. Kuhn, however, thought that unquestioning adherence to the theories of the day is proper; at least for ‘normal scientists’. In short, the former thought that dominant theories should be attacked, whereas the latter thought that they should be developed and defended (for the vast majority of the time). -/- Both seem to have missed a trick, however, due to their apparent insistence that each individual (...) scientist should fulfil similar functions (at any given point in time). The trick is to consider science at the group level; and doing so shows how puzzle solving and ‘offensive’ critical activity can simultaneously have a legitimate place in science. This analysis shifts the focus of the debate. The crucial question becomes ‘How should the balance between functions be struck?’. (shrink)

When is a law too idealized to be usefully applied to a specific situation? To answer this question, this essay considers a law in hydrogeology called Darcy''s Law, both as it is used in what is called the symmetric-cone model, and as it is used in equations to determine a well''s groundwater velocity and hydraulic conductivity. After discussing Darcy''s law and its applications, the essay concludes that this idealized law, as well as associated models and equations in hydrogeology, are not (...) realistic in the sense required by the D-N account. They exhibit what McMullin calls mathematical idealization, construct idealization, empirical-causal idealization, and subjunctive-causal idealization. Yet this lack of realism in hydrogeology is problematic for reasons unrelated to the status of the D-N account. These idealizations are also problematic in applied situations. Their problems require developing two supplemental criteria, necessary for their productive application. (shrink)

Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) (...) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology development work being undertaken in support of scientific research. Ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But the ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, ontologies such as the GO are in different respects comparable to scientific theories, to scientific databases, and to scientific journal publications. Such a view implies a new conception of what is involved in the authoring, maintenance and application of ontologies in scientific contexts, and therewith also a new approach to the evaluation of ontologies and to the training of ontologists. (shrink)

Science's priority rule rewards those who are first to make a discovery, at the expense of all other scientists working towards the same goal, no matter how close they may be to making the same discovery. I propose an explanation of the priority rule that, better than previous explanations, accounts for the distinctive features of the rule. My explanation treats the priority system, and more generally, any scheme of rewards for scientific endeavor, as a device for achieving an allocation of (...) resources among different research programs that provides as much benefit as possible to society. I show that the priority system is especially well suited to finding an efficient allocation of resources in those situations, characteristic of scientific inquiry, in which any success in an endeavor subsequent to the first success brings little additional benefit to society. (shrink)

Evolutionary Developmental Biology (Evo-Devo) is philosophically fascinating because of its plurality of scientific “cultures” of practice and theory that continue making progress towards a better understanding of complex biological reality. In this chapter, through an examination of a variety of the scientific cultures pertinent to Evo-Devo, I show that Evo-Devo can be usefully understood as a /trading zone/ (Galison 1997). That is, a variety of disciplines, styles, and paradigms negotiate heavily with each other in the domain of Evo-Devo. I am (...) concerned with the differences, the interactions, and the relative openness and flexibility of these cultures. When are the cultures acting—individually or collectively—in ways that further research, empirically, theoretically, and ethically? When do they become imperialistic, in the sense of excluding and subordinating other cultures? I wish to develop a critical /assumption archeology/ (my term, following Michel Foucault, Ian Hacking, and Michael Friedman), which explores some of the key presuppositions standing behind or under or within each of these cultures. These assumptions ground the concepts, methods, and models of each culture. The goal of this chapter is to identify six cultures of Evo-Devo (three styles and three paradigms), and provide an initial archeology of their internal structure, and mutual relations, through the concept of trading zone. My main excavation site is Bonner (1982), founding text of Evo-Devo and product of the 1981 Dahlem “Evolution and Development” workshop, on which this 2011 anthology (and workshop) was also based. (shrink)

In this paper I investigate the prospects of integrated history and philosophy of science, by examining how philosophical issues concerning experimental practice and scientific realism can enrich the historical investigation of the careers of "hidden entities", entities that are not accessible to unmediated observation. Conversely, I suggest that the history of those entities has important lessons to teach to the philosophy of science. My overall aim is to illustrate the possibility of a fruitful two-way traffic between history and philosophy of (...) science. (shrink)

Abstract This paper provides an account of the experimental conditions required for establishing whether correlating or causally relevant factors are constitutive components of a mechanism connecting input (start) and output (finish) conditions. I argue that two-variable experiments, where both the initial conditions and a component postulated by the mechanism are simultaneously manipulated on an independent basis, are usually required in order to differentiate between correlating or causally relevant factors and constitutively relevant ones. Based on a typical research project molecular biology, (...) a flowchart model detailing typical stages in the formulation and testing of hypotheses about mechanistic components is also developed. Content Type Journal Article Category Original paper in Philosophy of Biology Pages 1-17 DOI 10.1007/s13194-011-0045-3 Authors Tudor M. Baetu, Department of Philosophy, University of Maryland, College Park, MD, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912. (shrink)

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)

In Experiment, Right or Wrong, Allan Franklin continues his investigation of the history and philosophy of experiment presented in his previous book, The Neglect of Experiment. In this new study, Franklin considers the fallibility and corrigibility of experimental results and presents detailed histories of two such episodes: 1) the experiment and the development of the theory of weak interactions from Fermi's theory in 1934 to the V-A theory of 1957 and 2) atomic parity violation experiments and the Weinberg-Salam unified theory (...) of electroweak interactions of the 1970s and 1980s. In these episodes Franklin demonstrates not only that experimental results can be wrong, but also that theoretical calculations and the comparison between experiment and theory can also be incorrect. In the second episode, Franklin contrasts his view of an "evidence model" of science in which questions of theory choice, confirmation, and refutation are decided on the basis of reliable experimental evidence, with that proposed by the social constructivists. (shrink)

This book describes how scientists bring their own interests and passions to their work, illustrates the dynamics between researchers and the research community ...

"This book . . . is everything a philosophical tome should be: timely, important, factually informed, responsive to the scholarly literature, analytical, scrupulously fair, and rigorously, vigorously argued. It is, if I may say so, a model specimen of practical ethics." Keith Burgess-Jackson Ethics and the Environment).

Biomedical researchers claim there is significant biomedical information about humans which can be discovered only through experiments on intact animal systems (AMA p. 2). Although epidemiological studies, computer simulations, clinical investigation, and cell and tissue cultures have become important weapons in the biomedical scientists' arsenal, these are primarily "adjuncts to the use of animals in research" (Sigma Xi p. 76). Controlled laboratory experiments are the core of the scientific enterprise. Biomedical researchers claim these should be conducted on intact biological systems, (...) whole animals. By observing the effects of various stimuli in non-human animals, we can form legitimate expectations about the likely effects of these stimuli in humans. Perhaps more importantly, we can understand the biomedical condition's causal mechanisms. (shrink)

Biomedical experimentation on animals is justified, researchers say, because of its enormous benefits to human being. Sure an imals die a nd suffer , but that is m orally insignificant since the benefits of research incalculably outweigh the evils. Although this utilitarian claim appears straightforward and uncontroversial, it is neither straightforw ard n ot uncontroversial. This defense of animal experimentation is like ly to succeed only by rejecting three widely held moral presumptions. W e identify those presumptions and explain their (...) relevance to the justification of animal experimentation. We argue that even if non-human animals have con side rable less moral worth than humans, experimentation is justified only if its benefits are overwhelming. By building on arguments offered in earlier papers, we show that research ers c ann ot substantiate their claims of behalf of animal research. We conclude that there is currently no acceptable utilitarian defense of animal experimentation. Moreover, it is unlikely that they could be one. Since most apologists of animal experimentation rely on utilitarian justifications of their practice, it appears that biomedical experimentation on animals is not morally justified. (shrink)

Claude Bernard, the father of scientific physiology, believed that if medicine was to become truly scientiifc, it would have to be based on rigorous and controlled animal experiments. Bernard instituted a paradigm which has shaped physiological practice for most of the twentieth century. ln this paper we examine how Bernards commitment to hypothetico-deductivism and determinism led to (a) his rejection of the theory of evolution; (b) his minima/ization of the role of clinical medicine and epidemiological studies; and (c) his conclusion (...) that experiments on nonhuman animals were, "entirely conclusive for the toxicology and hygiene of man". We examine some negative consequences of Bernardianism for twentieth century medicine, and argue that physio/ogy's continued adherence to Bernardianism has caused it to diverge from the other biological sciences which have become increasingly infused with evolutionary theory. (shrink)

First half of book presents fundamental mathematical definitions, concepts and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text, numerous worked examples with step-by-step presentation. 116 tables.

This article assesses two major conceptual arguments against theories of choice.The first argument concerns the circularity of belief-desire psychology, on which decision theory is based. The second argument concerns the normativity arising from the concept of rationality. Each argument is evaluated against experimental practice in economics and psychology, and it is concluded that both arguments fail to establish their skeptical conclusion that there can be no science of intentional human actions.

I examine the role of inference from experiment in theory building. What are the options open to the scientific community when faced with an experimental result that appears to be in conflict with accepted theory? I distinguish, in Laudan’s (1977), Nickels’s (1981), and Franklin’s (1993) sense, between the context of pursuit and the context of justification of a scientific theory. Making this distinction allows for a productive middle position between epistemic realism and constructivism. The decision to pursue a new or (...) a revised theory in response to the new evidence may not be fully rationally determined. Nonetheless, it is possible to distinguish the question of whether there is reason to pursue a theory from the question of whether that theory, once it has been pursued over time, solves a problem of interest to science. I argue that, in this context, there is a solid way to distinguish between the contexts of pursuit and of justification, on the basis of a theory’s evidential support and problem-solving ability. (shrink)

Experiments may not reveal their full import at the time that they are performed. The scientists who perform them usually are testing a specific hypothesis and quite often have specific expectations limiting the possible inferences that can be drawn from the experiment. Nonetheless, as Hacking has said, experiments have lives of their own. Those lives do not end with the initial report of the results and consequences of the experiment. Going back and rethinking the consequences of the experiment in a (...) new context, theoretical or empirical, has great merit as a strategy for investigation and for scientific problem analysis. I apply this analysis to the interplay between Fizeau’s classic optical experiments and the building of special relativity. Einstein’s understanding of the problems facing classical electrodynamics and optics, in part, was informed by Fizeau’s 1851 experiments. However, between 1851 and 1905, Fizeau’s experiments were duplicated and reinterpreted by a succession of scientists, including Hertz, Lorentz, and Michelson. Einstein’s analysis of the consequences of the experiments is tied closely to this theoretical and experimental tradition. However, Einstein’s own inferences from the experiments differ greatly from the inferences drawn by others in that tradition. (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)

Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is conceptual (...) clarification, with a redefinition of concepts central to the understanding of the phenomenon and the conditions of its occurrence. (shrink)

Making sense of modeling: beyond representation Content Type Journal Article Category Original paper in Philosophy of Science Pages 335-352 DOI 10.1007/s13194-011-0032-8 Authors Isabelle Peschard, Philosophy Department, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 3.

Experimenters sometimes insist that it is unwise to examine data before determining how to analyze them, as it creates the potential for biased results. I explore the rationale behind this methodological guideline from the standpoint of an error statistical theory of evidence, and I discuss a method of evaluating evidence in some contexts when this predesignation rule has been violated. I illustrate the problem of potential bias, and the method by which it may be addressed, with an example from the (...) search for the top quark. A point in favor of the error statistical theory is its ability, demonstrated here, to explicate such methodological problems and suggest solutions, within the framework of an objective theory of evidence. (shrink)

Contrary to the claim that measurement standards are absolutely accurate by definition, I argue that unit definitions do not completely fix the referents of unit terms. Instead, idealized models play a crucial semantic role in coordinating the theoretical definition of a unit with its multiple concrete realizations. The accuracy of realizations is evaluated by comparing them to each other in light of their respective models. The epistemic credentials of this method are examined and illustrated through an analysis of the contemporary (...) standardization of time. I distinguish among five senses of ‘measurement accuracy’ and clarify how idealizations enable the assessment of accuracy in each sense. (shrink)

This paper defends a realist interpretation of theories and a modest realism concerning the existence of quantities as providing the best account both of the logic of quantity concepts and of scientific measurement practices. Various operationist analyses of measurement are shown to be inadequate accounts of measurement practices used by scientists. We argue, furthermore, that appeals to implicit definitions to provide meaning for theoretical terms over and above operational definitions fail because implicit definitions cannot generate the requisite descriptive content. The (...) special case of establishing a temperature scale is examined to show that nonrealist accounts fail to provide insight into the theoretical connections that scientific laws postulate to hold among quantities. (shrink)

In this paper we motivate and develop the analytic theory of measurement, in which autonomously specified algebras of quantities (together with the resources of mathematical analysis) are used as a unified mathematical framework for modeling (a) the time-dependent behavior of natural systems, (b) interactions between natural systems and measuring instruments, (c) error and uncertainty in measurement, and (d) the formal propositional language for describing and reasoning about measurement results. We also discuss how a celebrated theorem in analysis, known as Gelfand (...) representation, guarantees that autonomously specified algebras of quantities can be interpreted as algebras of observables on a suitable state space. Such an interpretation is then used to support (i) a realist conception of quantities as objective characteristics of natural systems, and (ii) a realist conception of measurement results (evaluations of quantities) as determined by and descriptive of the states of a target natural system. As a way of motivating the analytic approach to measurement, we begin with a discussion of some serious philosophical and theoretical problems facing the well-known representational theory of measurement. We then explain why we consider the analytic approach, which avoids all these problems, to be far more attractive on both philosophical and theoretical grounds. (shrink)

Measurement is a process aimed at acquiring and codifying information about properties of empirical entities. In this paper we provide an interpretation of such a process comparing it with what is nowadays considered the standard measurement theory, i.e., representational theory of measurement. It is maintained here that this theory has its own merits but it is incomplete and too abstract, its main weakness being the scant attention reserved to the empirical side of measurement, i.e., to measurement systems and to the (...) ways in which the interactions of such systems with the entities under measurement provide a structure to an empirical domain. In particular it is claimed that (1) it is on the ground of the interaction with a measurement system that a partition can be induced on the domain of entities under measurement and that relations among such entities can be established, and that (2) it is the usage of measurement systems that guarantees a degree of objectivity and intersubjectivity to measurement results. As modeled in this paper, measurement systems link the abstract theory of measuring, as developed in representational terms, and the practice of measuring, as coded in standard documents such as the International Vocabulary of Metrology. (shrink)

The concept system around ‘quantity’ and ‘quantity value’ is fundamental for measurement science, but some very basic issues are still open on such concepts and their relations. This paper proposes a duality between quantities and quantity values, a proposal that simplifies their characterization and makes it consistent.

An appropriate characterization of property types is an important topic for measurement science. On the basis of a set-theoretic model of evaluation and measurement processes, the paper introduces the operative concept of property evaluation type, and discusses how property types are related to, and in fact can be derived from, property evaluation types, by finally analyzing the consequences of these distinctions for the concepts of ‘property’ used in the International Vocabulary of Metrology – Basic and General Concepts and Associated Terms (...) (VIM3). (shrink)

An appropriate characterization of property types is an important topic for measurement science. This paper proposes to derive them from evaluation types, and analyzes the consequences of this position for the VIM3.

A description is given of the quantitative-qualitative distinction for terms in theories of measurable attributes, and, adjoined to that account, a suggestion is made concerning the sense in which empirical relational systems have an empirical attribute as their topic or focus. Since this characterization of quantitative terms, relative to a partition, makes no explicit reference to numbers, concatenation operations, or ordering relations, we show how our results are related to some standard theorems in the literature. Analogs of representation and uniqueness (...) theorems are proved, and the notions of exact quantitative term and the underlying attribute of a quantitative term, are described and studied. (shrink)

This collection of six essays centers on Professor Koyre;'s great theme: the relative importance of metaphysics and observation, with controlled experiment a kind of marriage between the two. Professor Koyre;'s thesis might be summed up as a claim that when one is seeking to explain the scientific revolution, attention must be concentrated on the philosophical outlook of the scientist and away from speculative theories. At the time of his death, Alexandre Koyre; was a professor at the Ecole Pratique des Hautes (...) Études (Sorbonne) and a memeber of the Institute for Advanced Study in Princeton. (shrink)

Part of the scientific enterprise is to measure the material world and to explain its dynamics by means of models. However, not only is measurability of the world limited, analyzability of models is so, too. Most often, computer simulations offer a way out of this epistemic bottleneck. They instantiate the model and may help to analyze it. In relation to the material world a simulation may be regarded as a kind of a “non-material scale model”. Like any other scale model, (...) it does not per se give any scientific explanation but is first in itself an object of scientific enquiry, a world. Since this world is numerical, it is a priori measurable. Its role in scientific explanation will be discussed. (shrink)

Measurement is fundamental to all the sciences, the behavioural and social as well as the physical and in the latter its results provide our paradigms of 'objective fact'. But the basis and justification of measurement is not well understood and is often simply taken for granted. Henry Kyburg Jr proposes here an original, carefully worked out theory of the foundations of measurement, to show how quantities can be defined, why certain mathematical structures are appropriate to them and what meaning attaches (...) to the results generated. Crucial to his approach is the notion of error - it can not be eliminated entirely from its introduction and control, her argues, arises the very possibility of measurement. Professor Kyburg's approach emphasises the empirical process of making measurements. In developing it he discusses vital questions concerning the general connection between a scientific theory and the results which support it (or fail to). (shrink)

Quantities are naturally viewed as functions, whose arguments may be construed as situations, events, objects, etc. We explore the question of the range of these functions: should it be construed as the real numbers (or some subset thereof)? This is Carnap's view. It has attractive features, specifically, what Carnap views as ontological economy. Or should the range of a quantity be a set of magnitudes? This may have been Helmholtz's view, and it, too, has attractive features. It reveals the close (...) connection between measurement and natural law, it makes dimensional analysis intelligible, and explains the concern of scientists and engineers with units in equations. It leaves the philosophical problem of the relation between the structure of magnitudes and the structure of the reals. What explains it? And is it always the same? We will argue that on the whole, construing the values of quantities as magnitudes has some advantages, and that (as Helmholtz seems to suggest in "Numbering and Measuring from an Epistemological Viewpoint") the relation between magnitudes and real numbers can be based on foundational similarities of structure. (shrink)

The distinction between data and phenomena introduced by Bogen and Woodward (Philosophical Review 97(3):303–352, 1988) was meant to help accounting for scientific practice, especially in relation with scientific theory testing. Their article and the subsequent discussion is primarily viewed as internal to philosophy of science. We shall argue that the data/phenomena distinction can be used much more broadly in modelling processes in philosophy.

Suppose that entities composed of two independent components are qualitatively ordered by a relation that satisfies the axioms of conjoint measurement. Suppose, in addition, that each component has a concatenation operation that, together either with the ordering induced on the component by the conjoint ordering or with its converse, satisfies the axioms of extensive measurement. Without further assumptions, nothing can be said about the relation between the numerical scales constructed from the two measurement theories except that they are strictly monotonic. (...) An axiom is stated that relates the two types of measurement theories, seems to cover all cases of interest in physics, and is sufficient to establish that (the multiplicative form of) the conjoint measurement scales are power functions of the extensive measurement scales. (shrink)

Given the common assumption that measurement plays an important role in the foundation of science, the paper analyzes the possibility that Measurement Science, and therefore measurement itself, can be properly founded. The realist and the representational positions are analyzed at this regards: the conclusion, that such positions unavoidably lead to paradoxical situations, opens the discussion for a new epistemology of measurement, whose characteristics and interpretation are sketched here but are still largely matter of investigation.

The paper introduces what is deemed as the general epistemological problem of measurement: what characterizes measurement with respect to generic evaluation? It also analyzes the fundamental positions that have been maintained about this issue, thus presenting some sketches for a conceptual history of measurement. This characterization, in which three distinct standpoints are recognized, corresponding to a metaphysical, an anti-metaphysical, and relativistic period, allows us to introduce and briefly discuss some general issues on the current epistemological status of measurement science.

The paper introduces and formally defines a functional concept of a measuring system, on this basis characterizing the measurement as an evaluation performed by means of a calibrated measuring system. The distinction between exact and uncertain measurement is formalized in terms of the properties of the traceability chain joining the measuring system to the primary standard. The consequence is drawn that uncertain measurements lose the property of relation-preservation, on which the very concept of measurement is founded according to the representational (...) viewpoint. Finally, from the analysis of the inter-relations between calibration and measurement the fundamental reasons of the claimed objectivity and intersubjectivity of measurement are highlighted, a valuable epistemological result to characterize measurement as a particular kind of evaluation. (shrink)

Measurement in soft systems generally cannot exploit physical sensors as data acquisition devices. The emphasis in this case is instead on how to choose the appropriate indicators and to combine their values so to obtain an overall result, interpreted as the value of a property, i.e., the measurand, for the system under analysis. This paper aims at discussing the epistemological conditions of the claim that such a process is a measurement, and performance evaluation is the case introduced to support the (...) analysis, performed in systematic comparison with the paradigm of measurement of physical quantities. Some background questions arising here are: – Are the chosen indicators appropriate performance indicators? – Do such indicators convey complete and non-redundant information on performance? – Does the chosen combination rule generate results suitably interpretable as performance values? And enlarging the focus: – Does the obtained value specifically convey information on the system under analysis, instead of some different entity (typically including the subject who is evaluating)? Operatively: would different subjects evaluate the same system in the same way? i.e., is the obtained information objective? – Does the obtained value convey information that is interpretable in the same way by different subjects? Operatively: would different subjects who have agreed on a decision procedure make the same decision from the same performance information? i.e., is the obtained information intersubjective? Any well founded positive answers to these questions significantly support a structural interpretation of measurement encompassing both physical and soft measurement. (shrink)

This paper discusses a relational modeling of measurement which is complementary to the standard representational point of view: by focusing on the experimental character of the measurand-related comparison between objects, this modeling emphasizes the role of the measuring systems as the devices which operatively perform such a comparison. The non-idealities of the operation are formalized in terms of non-transitivity of the substitutability relation between measured objects, due to the uncertainty on the measurand value remaining after the measurement. The metrological structure (...) of traceability is shown to be an effective solution to cope with the problem of the general non-transitivity of measurement results. A preliminary theory is introduced as a possible formalization for the presented model. (shrink)

Bogen and Woodward claim that the function of scientific theories is to account for 'phenomena', which they describe both as investigator-independent constituents of the world and as corresponding to patterns in data sets. I argue that, if phenomena are considered to correspond to patterns in data, it is inadmissible to regard them as investigator-independent entities. Bogen and Woodward's account of phenomena is thus incoherent. I offer an alternative account, according to which phenomena are investigator-relative entities. All the infinitely many patterns (...) that data sets exhibit have equal intrinsic claim to the status of phenomenon: each investigator may stipulate which patterns correspond to phenomena for him or her. My notion of phenomena accords better both with experimental practice and with the historical development of science. (shrink)

The need for quantitative measurement represents a unifying bond that links all the physical, biological, and social sciences. Measurements of such disparate phenomena as subatomic masses, uncertainty, information, and human values share common features whose explication is central to the achievement of foundational work in any particular mathematical science as well as for the development of a coherent philosophy of science. This book presents a theory of measurement, one that is "abstract" in that it is concerned with highly general axiomatizations (...) of empirical and qualitative settings and how these can be represented quantitatively. It was inspired by, and represents a generalization and extension of, the last major research work in this field, Foundations of Measurement Vol. I, by Krantz, Luce, Suppes, and Tversky published in 1971. (shrink)

Axiomatizations of measurement systems usually require an axiom--called an Archimedean axiom--that allows quantities to be compared. This type of axiom has a different form from the other measurement axioms, and cannot--except in the most trivial cases--be empirically verified. In this paper, representation theorems for extensive measurement structures without Archimedean axioms are given. Such structures are represented in measurement spaces that are generalizations of the real number system. Furthermore, a precise description of "Archimedean axioms" is given and it is shown that (...) in all interesting cases "Archimedean axioms" are independent of other measurement axioms. (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)

This book provides an introduction to measurement theory for non-specialists and puts measurement in the social and behavioural sciences on a firm mathematical foundation. Results are applied to such topics as measurement of utility, psychophysical scaling and decision-making about pollution, energy, transportation and health. The results and questions presented should be of interest to both students and practising mathematicians since the author sets forth an area of mathematics unfamiliar to most mathematicians, but which has many potentially significant applications.

Some twenty years ago, Bogen and Woodward challenged one of the fundamental assumptions of the received view, namely the theory-observation dichotomy and argued for the introduction of the further category of scientific phenomena. The latter, Bogen and Woodward stressed, are usually unobservable and inferred from what is indeed observable, namely scientific data. Crucially, Bogen and Woodward claimed that theories predict and explain phenomena, but not data. But then, of course, the thesis of theory-ladenness, which has it that our observations are (...) influenced by the theories we hold, cannot apply. On the basis of two case studies, I want to show that this consequence of Bogen and Woodward’s account is rather unrealistic. More importantly, I also object against Bogen and Woodward’s view that the reliability of data, which constitutes the precondition for data-to-phenomena inferences, can be secured without the theory one seeks to test. The case studies I revisit have figured heavily in the publications of Bogen and Woodward and others: the discovery of weak neutral currents and the discovery of the zebra pattern of magnetic anomalies. I show that, in the latter case, data can be ignored if they appear to be irrelevant from a particular theoretical perspective (TLI) and that, in the former case, the tested theory can be critical for the assessment of the reliability of the data (TLA). I argue that both TLI and TLA are much stronger senses of theory-ladenness than the classical thesis and that neither TLI nor TLA can be accommodated within Bogen and Woodward’s account. (shrink)

Ordinary measurement using a standard scale, such as a ruler or a standard set of weights, has two fundamental properties. First, the results are approximate, for example, within 0.1 g. Second, the resulting indistinguishability is transitive, rather than nontransitive, as in the standard psychological comparative judgments without a scale. Qualitative axioms are given for structures having the two properties mentioned. A representation theorem is then proved in terms of upper and lower measures.

A carpet vendor has to measure her customer's living room for some new broadloom. She has forgotten her tape measure, but does have a meterstick. She lays the meterstick on the floor, snug up against the wall, with the left edge of the stick in one corner of the room. She then makes a pencil mark at the right edge. Next she shifts the stick right until the left edge of the stick is at her mark, and again marks the (...) right edge. She does this three times, but then finds that less than a full length remains to be measured. She turns the stick around so that the zero is now at the right side and lays it in the right corner and notes that her last pencil mark is at 70 cm. She concludes that the wall she is measuring is 3.7 meters in length. She then measures the opposite wall and concludes that it, too, is 3.7 meters in length. She then repeats the process for the remaining two opposite walls, and finds that they each measure 4.1 meters. To see if the room is rectangular, she runs a piece of twine from one corner to its opposite, pulls the twine taut and then cuts it to fit exactly. She then uses the same piece of twine on the other two corners to see if they are the same distance apart as the first two. The twine fits exactly. On the basis of these measurements, she.. (shrink)

Depending on different positions in the debate on scientific realism, there are various accounts of the phenomena of physics. For scientific realists like Bogen and Woodward, phenomena are matters of fact in nature, i.e., the effects explained and predicted by physical theories. For empiricists like van Fraassen, the phenomena of physics are the appearances observed or perceived by sensory experience. Constructivists, however, regard the phenomena of physics as artificial structures generated by experimental and mathematical methods. My paper investigates the historical (...) background of these different meanings of phenomenon in the traditions of physics and philosophy. In particular, I discuss Newton’s account of the phenomena and Bohr’s view of quantum phenomena, their relation to the philosophical discussion, and to data and evidence in current particle physics and quantum optics. (shrink)

Broadly stated, naïve realism is the attitude that the form of our outer experiences directly and literally correspond to the structure of the real world underlying these experiences. Naïve realism permeates our everyday thinking about, and ordinary language description of, the macroscopic world. It has undeniable pragmatic justification. However, as Descartes recognized centuries ago, philosophically speaking, naïve realism requires a justification. Physicists, nevertheless, simply assume naïve realism in interpreting the laboratory observations realistically. Thus, physicists do not find the philosophical issues (...) surrounding the problem of naïve realism to be any of relevance to the development of physics per se. The problem of scientific realism is seen to arise in a different context, that of justifying the idea that our best theories in physics pragmatically succeed because its abstract entities provide a true glimpse of the external world under investigation. (shrink)

This book describes how scientists bring their own interests and passions to their work, illustrates the dynamics between researchers and the research community ...

Increasingly encompassing models have been suggested for our world. Theories range from generally accepted to increasingly speculative to apparently bogus. The progression of theories from ego- to geo- to helio-centric models to universe and multiverse theories and beyond was accompanied by a dramatic increase in the sizes of the postulated worlds, with humans being expelled from their center to ever more remote and random locations. Rather than leading to a true theory of everything, this trend faces a turning point after (...) which the predictive power of such theories decreases (actually to zero). Incorporating the location and other capacities of the observer into such theories avoids this problem and allows to distinguish meaningful from predictively meaningless theories. This also leads to a truly complete theory of everything consisting of a (conventional objective) theory of everything plus a (novel subjective) observer process. The observer localization is neither based on the controversial anthropic principle, nor has it anything to do with the quantum-mechanical observation process. The suggested principle is extended to more practical (partial, approximate, probabilistic, parametric) world models (rather than theories of everything). Finally, I provide a justification of Ockham's razor, and criticize the anthropic principle, the doomsday argument, the no free lunch theorem, and the falsifiability dogma.", . (shrink)

The progression of theories suggested for our world, from ego- to geo- to helio-centric models to universe and multiverse theories and beyond, shows one tendency: The size of the described worlds increases, with humans being expelled from their center to ever more remote and random locations. If pushed too far, a potential theory of everything (TOE) is actually more a theories of nothing (TON). Indeed such theories have already been developed. I show that including observer localization into such theories is (...) necessary and sufficient to avoid this problem. I develop a quantitative recipe to identify TOEs and distinguish them from TONs and theories in-between. This precisely shows what the problem is with some recently suggested universal TOEs. (shrink)

Assuming an essential difference between scientific data and phenomena, this paper argues for the view that we have to understand how empirical findings get transformed into scientific phenomena. The work of scientists is seen as largely consisting in constructing these phenomena which are then utilized in more abstract theories. It is claimed that these matters are of importance for discussions of theory choice and progress in science. A case study is presented as a starting point: paleomagnetism and the use of (...) paleomagnetic data in early discussions of continental drift. Some general features of this study are presented in formalized language. It is suggested that the presentation given is particularly suited for a semantic conception of theories. Even though the construction of scientific phenomena is the main topic of this paper, the view presented here is more adapted to realism than social constructivism. (shrink)

This collection of six essays centers on Professor Koyre;'s great theme: the relative importance of metaphysics and observation, with controlled experiment a kind of marriage between the two. Professor Koyre;'s thesis might be summed up as a claim that when one is seeking to explain the scientific revolution, attention must be concentrated on the philosophical outlook of the scientist and away from speculative theories. At the time of his death, Alexandre Koyre; was a professor at the Ecole Pratique des Hautes (...) Études (Sorbonne) and a memeber of the Institute for Advanced Study in Princeton. (shrink)

The distinction between data and phenomena introduced by Bogen and Woodward (Philosophical Review 97(3):303–352, 1988) was meant to help accounting for scientific practice, especially in relation with scientific theory testing. Their article and the subsequent discussion is primarily viewed as internal to philosophy of science. We shall argue that the data/phenomena distinction can be used much more broadly in modelling processes in philosophy.

Bogen and Woodward claim that the function of scientific theories is to account for 'phenomena', which they describe both as investigator-independent constituents of the world and as corresponding to patterns in data sets. I argue that, if phenomena are considered to correspond to patterns in data, it is inadmissible to regard them as investigator-independent entities. Bogen and Woodward's account of phenomena is thus incoherent. I offer an alternative account, according to which phenomena are investigator-relative entities. All the infinitely many patterns (...) that data sets exhibit have equal intrinsic claim to the status of phenomenon: each investigator may stipulate which patterns correspond to phenomena for him or her. My notion of phenomena accords better both with experimental practice and with the historical development of science. (shrink)

Some twenty years ago, Bogen and Woodward challenged one of the fundamental assumptions of the received view, namely the theory-observation dichotomy and argued for the introduction of the further category of scientific phenomena. The latter, Bogen and Woodward stressed, are usually unobservable and inferred from what is indeed observable, namely scientific data. Crucially, Bogen and Woodward claimed that theories predict and explain phenomena, but not data. But then, of course, the thesis of theory-ladenness, which has it that our observations are (...) influenced by the theories we hold, cannot apply. On the basis of two case studies, I want to show that this consequence of Bogen and Woodward’s account is rather unrealistic. More importantly, I also object against Bogen and Woodward’s view that the reliability of data, which constitutes the precondition for data-to-phenomena inferences, can be secured without the theory one seeks to test. The case studies I revisit have figured heavily in the publications of Bogen and Woodward and others: the discovery of weak neutral currents and the discovery of the zebra pattern of magnetic anomalies. I show that, in the latter case, data can be ignored if they appear to be irrelevant from a particular theoretical perspective (TLI) and that, in the former case, the tested theory can be critical for the assessment of the reliability of the data (TLA). I argue that both TLI and TLA are much stronger senses of theory-ladenness than the classical thesis and that neither TLI nor TLA can be accommodated within Bogen and Woodward’s account. (shrink)

The received view of an ad hochypothesis is that it accounts for only the observation(s) it was designed to account for, and so non-ad hocness is generally held to be necessary or important for an introduced hypothesis or modification to a theory. Attempts by Popper and several others to convincingly explicate this view, however, prove to be unsuccessful or of doubtful value, and familiar and firmer criteria for evaluating the hypotheses or modified theories so classified are characteristically available. These points (...) are obscured largely because the received view fails to adequately separate psychology from methodology or to recognise ambiguities in the use of ''ad hoc''. (shrink)

Chaos-related obstructions to predictability have been used to challenge accounts of theory validation based on the agreement between theoretical predictions and experimental data (Rueger & Sharp, 1996. The British Journal for the Philosophy of Science, 47, 93–112; Koperski, 1998. Philosophy of Science, 40, 194–212). These challenges are incomplete in two respects: (a) they do not show that chaotic regimes are unpredictable in principle (i.e., with unbounded resources) and, as a result, that there is something conceptually wrong with idealized expectations of (...) correct predictions from acceptable theories, and (b) they do not explore whether chaos-induced predictive failures of deterministic models can be remedied by stochastic modeling. In this paper we appeal to an asymptotic analysis of state space trajectories and their numerical approximations to show that chaotic regimes are deterministically unpredictable even with unbounded resources. Additionally, we explain why stochastic models of chaotic systems, while predictively successful in some cases, are in general predictively as limited as deterministic ones. We conclude by suggesting that the way in which scientists deal with such principled obstructions to predictability calls for a more comprehensive approach to theory validation, on which experimental testing is augmented by a multifaceted mathematical analysis of theoretical models, capable of identifying chaos-related predictive failures as due to principled limitations which the world itself imposes on any less-than-omniscient epistemic access to some natural systems. (shrink)

Our aim in this paper is to bring the woefully neglected literature on predictive modeling to bear on some central questions in the philosophy of science. The lesson of this literature is straightforward: For a very wide range of prediction problems, statistical prediction rules (SPRs), often rules that are very easy to implement, make predictions than are as reliable as, and typically more reliable than, human experts. We will argue that the success of SPRs forces us to reconsider our views (...) about what is involved in understanding, explanation, good reasoning, and about how we ought to do philosophy of science. (shrink)

In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...) I develop is a version of common cause explanation. Common cause explanation has long been vindicated by appealing to the principle of the common cause. Many philosophers of science (e.g., Sober and Tucker) find this principle problematic, however, because they believe that it is either purely methodological or strictly metaphysical. I defend a third possibility: the principle of the common cause derives its justification from a physically pervasive time asymmetry of causation (a.k.a. the asymmetry of overdetermination). I argue that explicating the principle of the common cause in terms of the asymmetry of overdetermination illuminates some otherwise puzzling features of the practices of historical natural scientists. (shrink)

According to the no miracles argument, scientific realism provides the only satisfactory explanation of the predictive success of science. It is argued in the present article that a different explanatory strategy, based on the posit of limitations to the underdetermination of scientific theory building by the available empirical data, offers a more convincing understanding of scientific success.

The paper provides a formal proof that efficient estimates of parameters, which vary as as little as possible when measurements are repeated, may be expected to provide more accurate predictions. The definition of predictive accuracy is motivated by the work of Akaike (1973). Surprisingly, the same explanation provides a novel solution for a well known problem for standard theories of scientific confirmation — the Ravens Paradox. This is significant in light of the fact that standard Bayesian analyses of the paradox (...) fail to account for the predictive utility of universal laws like All ravens are black. (shrink)

This paper investigates whether there is a discrepancy between the stated and actual aims in biomechanical research, particularly with respect to hypothesis testing. We present an analysis of one hundred papers recently published in The Journal of Experimental Biology and Journal of Biomechanics, and examine the prevalence of papers which (a) have hypothesis testing as a stated aim, (b) contain hypothesis testing claims that appear to be purely presentational (i.e. which seem not to have influenced the actual study), and (c) (...) have exploration as a stated aim. We found that whereas no papers had exploration as a stated aim, 58% of papers had hypothesis testing as a stated aim. We had strong suspicions, at the bare minimum, that presentational hypotheses were present in 31% of the papers in this latter group. (shrink)

One of the fundamental questions of life sciences is one of whether there are genuinely random biological processes. An affirmative or negative answer to this question may have important methodological consequences. It appears that a number of biological processes are explicitly classified as random. One of them is the so-called somatic hypermutation. However, closer analysis of somatic hypermutation reveals that it is not a genuinely random process. Somatic hypermutation is called random because the exact outcome of this process is difficult (...) to predict in practice. The case of somatic hypermutation suggests that there may be no scientific evidence of a single case of ontologically random process in the biological world. (shrink)