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)

This article offers a simple technical resolution to the problem of induction, which is to say that general facts are not always inferred from observations of particular facts, but are themselves sometimes defeasibly observed. The article suggests a holistic account of observation that allows for general statements in empirical theories to be interpreted as observation reports, in place of the common but arguably obsolete idea that observations are exclusively particular. Predictions and other particular statements about unobservable facts can then appear (...) as deductive consequences of such general observation statements, rather than inductive consequences of other particular statements. This semantic shift resolves the problem by eliminating induction as a basic form of inference, and folding the justification of general beliefs into the more basic problem of perception. (shrink)

Fodor and LePore's reconstruction of the semantic holism debate in terms of "atomism" and "anatomism" is inadequate: it fails to highlight the important issue of how intentional contents are individuated, and excludes or obscures several possible positions on the metaphysics of content. One such position, "weak sociabilism" is important because it addresses concerns of Fodor and LePore's molecularist critics about conditions for possession of concepts, without abandoning atomism about content individuation. Properties like DEMOCRACY may be "theoretical" in the following sense: (...) only devices capable of inference can come to be selectively sensitive to such properties. Thus, such concepts cannot be punctate, although their contents are individuated, as atomism requires, independently of their conceptual connections. (shrink)

A normative constraint on theories about objects which we take to be real is explored: such theories are required to track the properties of the objects which they are theories of. Epistemic views in which observation (and generalizations of it) play a central role, and holist views which see epistemic virtues as applicable only to whole theories, are contrasted in the light of this constraint. It's argued that global-style epistemic virtues can't meet the constraint, although (certain) epistemic views within which (...) observation (and, more generally, thick epistemic access) are centralized do meet it. (shrink)

In his 1927 Analysis of Matter and elsewhere, Russell argued that we can successfully infer the structure of the external world from that of our explanatory schemes. While nothing guarantees that the intrinsic qualities of experiences are shared by their objects, he held that the relations tying together those relata perforce mirror relations that actually obtain (these being expressible in the formal idiom of the Principia Mathematica). This claim was subsequently criticized by the Cambridge mathematician Max Newman as true but (...) trivial, insofar as from a closed body of observations (or “Ramsey sentence”) one can always generate other equally-satisfactory networks of relations, provided they respect the original set’s cardinality. Since any model thus generated will be empirically adequate, “[t]he defence is therefore driven back from the fairly safe fictitious-real classification to the much less tenable ‘trivial’ and ‘important’” (Newman 1928). Given the definitional rigour afforded by the initial appeal to isomorphism (via one-to-one correspondences in extension), the received assessment, shared by Russell himself, is that retreating to a pragmatic adjudication would betoken a fatal blow. However, I suggest that reliance on “importance” can be avoided if we incorporate an impersonal criterion of diachronic precedence. When collecting observations, an ordinality emerges alongside the cardinality which gives that underived structure an irrevocable epistemological privilege. Hence, I argue that, all other things being equal, any construct parasitic on an antecedent theory ought to be regarded as inferior/dispensable, since it was generated by an algorithm lacking the world-involving pedigree of its host structure. (shrink)

In this paper I argue that Poincaré’s acceptance of the atom does not indicate a shift from instrumentalism to scientific realism. I examine the implications of Poincaré’s acceptance of the existence of the atom for our current understanding of his philosophy of science. Specifically, how can we understand Poincaré’s acceptance of the atom in structural realist terms? I examine his 1912 paper carefully and suggest that it does not entail scientific realism in the sense of acceptance of the fundamental existence (...) of atoms but rather, argues against fundamental entities. I argue that Poincaré’s paper motivates a non-fundamentalist view about the world, and that this is compatible with his structuralism. (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)

There are two ways to do the unexpected. The banal way—let's call it the expectedly unexpected—is simply to chart the waters of what is and is not done, and then set out to do something different. For a philosopher, this can be done by embracing a method of non sequitor or by perhaps inverting some strongly held assumption of the field. The more interesting way— the unexpectedly unexpected—is to transform the expectations themselves; to do something new and contextualize it in (...) such a way that it not only makes perfect sense, but has the audience scratching their heads and saying, “Of course!” To do the unexpectedly unexpected on a regular basis is the true mark of genius. It recalls Kant's characterization of the genius as the one who not merely follows or breaks the rules of art but that, “Genius is the natural endowment that gives the rule to art.” We would not like to make the bold claim that Paul M. Churchland (PMC) is a philosophical genius of Kantian standards, but he sometimes achieves the unexpectedly unexpected and his position on the issue of scientific realism is a fine example of this. Given other views he holds and the philosophical forebears he holds dear, one might expect him to embrace an antirealism with respect to the posits of scientific theories. But, quite to the contrary, Churchland is one of the strongest contemporary philosophical voices on behalf of scientific realism. And, as we will discuss in this chapter, a closer look at this reasoning reveals that his realism is not perverse, it is exactly the sort of position he should be expected to hold, if only we understand the philosophical issues correctly. (shrink)

The 20th century philosophy of science began on a positivistic note. Its focal point was scientific explanation and the hypothetico-deductive (HD) framework of explanation was proposed as the standard of what is meant by “science.” HD framework, its inductive and statistical variants, and other logic-based approaches to modeling scientific explanation were developed long before the dawn of the information age. Since that time, the volume of observational data and power of high performance computing have increased by several orders of magnitude (...) and reshaped the practice and concept of science, and indeed, the philosophy of science. A new observational-inductive (OI) framework for scientific research is emerging due to recent developments in sensors, data systems, computers, and knowledge discovery techniques. We examine the nature of these changes and their impact on the question of what is meant by “science” after discussing five examples of the OI framework, and conclude that the HD and OI frameworks are complementary and synergistic. (shrink)

A stalwart view in the philosophy of science holds that, even when broadly construed so as to include theoretical auxiliaries, theories cannot make direct contact with observations. This view owes much to Bogen and Woodward’s (1988) influential distinction between data and phenomena. According to them, data are typically the kind of things that are observable or measurable like "bubble chamber photographs, patterns of discharge in electronic particle detectors and records of reaction times and error rates in various psychological experiments" (p. (...) 306). Phenomena are physical processes that are typically unobservable. Examples of the latter category include "weak neutral currents, the decay of the proton, and chunking and recency effects in human memory" (ibid.). Theories, in Bogen and Woodward’s view, are utilised to systematically explain, infer and predict phenomena, not data (pp. 305-306). The relationship between theories and data is rather indirect. Data count as evidence for phenomena and the latter in turn count as evidence for theories. This view is becoming increasingly influential (e.g. Prajit K. Basu (2003), Stathis Psillos (2004) and Mauricio Suárez (2005)). In this paper I argue contrary to this view that in various significant and well-known cases theories do make direct contact with the help of suitable auxiliaries. (shrink)

In a recent paper James Bogen and James Woodward denounce a set of views on confirmation that they collectively brand ‘IRS’. The supporters of these views cast confirmation in terms of Inferential Relations between observational and theoretical Sentences. Against IRS accounts of confirmation, Bogen and Woodward unveil two main objections: (a) inferential relations are not necessary to model confirmation relations since many data are neither in sentential form nor can they be put in such a form and (b) inferential relations (...) are not sufficient to model confirmation relations because the former cannot capture evidentially relevant factors about the detection processes and instruments that generate the data. In this paper I have a two-fold aim: (i) to show that Bogen and Woodward fail to provide compelling grounds for the rejection of IRS models and (ii) to highlight some of the models’ neglected merits. (shrink)

The dangers of character reification for cladistic inference are explored. The identification and analysis of characters always involves theory-laden abstraction—there is no theory-free “view from nowhere.” Given theory-ladenness, and given a real world with actual objects and processes, how can we separate robustly real biological characters from uncritically reified characters? One way to avoid reification is through the employment of objectivity criteria that give us good methods for identifying robust primary homology statements. I identify six such criteria and explore each (...) with examples. Ultimately, it is important to minimize character reification, because poor character analysis leads to dismal cladograms, even when proper phylogenetic analysis is employed. Given the deep and systemic problems associated with character reification, it is ironic that philosophers have focused almost entirely on phylogenetic analysis and neglected character analysis. (shrink)

As data-intensive and computational science become increasingly established as the dominant mode of conducting scientific research, visualisations of data and of the outcomes of science become increasingly prominent in mediating knowledge in the scientific arena. This position piece advocates that more attention should be paid to the epistemological role of visualisations beyond their being a cognitive aid to understanding, but as playing a crucial role in the formation of evidence for scientific claims. The new generation of computational and informational visualisations (...) and imaging techniques challenges the philosophy of science to re-think its position on three key distinctions: the qualitative/quantitative distinction, the subjective/objective distinction, and the causal/non-causal distinction. (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)

The present paper claims that M. S. Tswett’s chromatographic adsorption analysis, which today is a ubiquitous and instrumentally sophisticated chemical technique, was either ignored or outright rejected by chemists and botanists in the first three decades of the twentieth century because it did not make sense in terms of accepted chemical theory or practice. Evidence for this claim is culled from consideration of the botanical and chemical context of Tswett’s technique as well as an analysis of the protracted debate over (...) Tswett’s chromatographic analysis of chlorophyll between him and Leon Marchlewski, a noted chlorophyll chemist of the period. In this way, the paper expands and amends what it calls the ‘textbook story’ of the early history of chromatography, examples of which may be found in historical notes in many textbooks of chemical instrumental analysis and numerous short articles in chemistry journals. The paper also provides an accessible introduction to the early history of chromatography for historians of science likely to know little or nothing about it. (shrink)

The 20th century philosophy of science began on a positivistic note. Its focal point was scientific explanation and the hypothetico-deductive (HD) framework of explanation was proposed as the standard of what is meant by “science.” HD framework, its inductive and statistical variants, and other logic-based approaches to modeling scientific explanation were developed long before the dawn of the information age. Since that time, the volume of observational data and power of high performance computing have increased by several orders of magnitude (...) and reshaped the practice and concept of science, and indeed, the philosophy of science. A new observational-inductive (OI) framework for scientific research is emerging due to recent developments in sensors, data systems, computers, and knowledge discovery techniques. We examine the nature of these changes and their impact on the question of what is meant by “science” after discussing five examples of the OI framework, and conclude that the HD and OI frameworks are complementary and synergistic. (shrink)