Interpretation, Constraint, and the Prospects of Scientific Realism I explore the interaction between theory-based interpretations of scientific evidence and constraints on theories provided by that evidence. Interpretation is often viewed as a source of error and a reason for scepticism about scientific results. But, I argue, while interpretation does generate epistemic risk, it also points to new sources of evidence that can constrain our theories. This is especially clear in the development of instrumentation that increases the range of our interactions (...) with nature. While the design of such instruments and the interpretation of their outputs are deeply dependent on theory-based interpretations, these outputs can still challenge those very theories. At the same time, theory-guided instrumentation provides us access to aspects of nature that we cannot study with our unaided senses. This access allows us to extend the range of evidence that we collect, and thus increases the constraints on our theories. As a result, theory-guided evidence collection has a positive impact on the prospects of scientific realism since these increasing constraints on our theories provide our only reason for thinking that we may be approaching the development of true theories. (shrink)

This work explores issues with the eliminativist formulation of ontic structural realism. An ontology that totally eliminates objects is found lacking by arguing, first, that the theoretical frameworks used to support the best arguments against an object-oriented ontology (quantum mechanics, relativity theory, quantum field theory) can be seen in every case as physical models of empty worlds, and therefore do not represent all the information that comes from science, and in particular from fundamental physics, which also includes information about local (...) interactions between objects. Secondly, by giving a critical assessment of the role of symmetries in these fundamental physical theories; and, lastly, by warning about unfounded metaphysical assumptions. An argument is made for a moderate form of structural realism instead, one in which objects play the fundamental role of representing symmetries and bearing their conserved charges, and of participating in the network of interactions observed in the world. (shrink)

The problem of natural kinds forms the busy crossroads where a number of larger problems meet: the problem of universals, the problem of induction and projectibility, the problem of natural laws and de re modalities, the problem of meaning and reference, the problem of intertheoretic reduction, the question of the aim of science, and the problem of scientific realism in general. Nor do these exhaust the list. Not surprisingly then, different writers confront a different ‘problem of natural kinds,’ depending on (...) which background issue is for them the principal issue at stake. The issues of essentialism, meaning, and reference, for example, have tended to dominate recent discussions of natural kinds. But evidently these are only part of the puzzle. (shrink)

The problem of natural kinds forms the busy crossroads where a number of larger problems meet: the problem of universals, the problem of induction and projectibility, the problem of natural laws and de re modalities, the problem of meaning and reference, the problem of intertheoretic reduction, the question of the aim of science, and the problem of scientific realism in general. Nor do these exhaust the list. Not surprisingly then, different writers confront a different ‘problem of natural kinds,’ depending on (...) which background issue is for them the principal issue at stake. The issues of essentialism, meaning, and reference, for example, have tended to dominate recent discussions of natural kinds. But evidently these are only part of the puzzle. (shrink)

I develop a concept of observability that pertains to qualities rather than objects: a quality is observable if it can be registered by human sensation (possibly with the aid of instruments) without involving optional interpretations. This concept supports a better description of observations in science and everyday life than the object-based observability concepts presupposing causal information-transfer from the object to the observer. It also allows a rehabilitation of the traditional empiricist distinction between observations and their interpretations, but without a presumption (...) that observations are infallible. Using this concept of observability, I also propose a re-formulation of constructive empiricism that is easier to defend against realist attacks, while open to reasonable realist intuitions. (shrink)

Operationalism and theoretical entities. The thesis of the“theory ladenness” of observation leads to an antinomy. In order to solve this antinomy a technical operationalism is sketched, according to which theories should in principle not contain anything that cannot be reduced to technical procedures. This implies the rejection of Quine's underdeterminacy thesis and of many views about the theoretical-observational distinction, e.g. neopositivistic views, van Fraassen's view, Sneed-Stegmüller's view. Then I argue for the following theses: 1. All scientific concepts are theory laden (...) in the sense that they allow us to anticipate possible experiences, but they have to be in principle fully observable, i.e. integrally convertible into operational-technical applications. 2. The observation/theory distinction can be maintained as a historical one: what is observable depends on the instruments that are available at any stage of the development of science. 3.In principle theoretical entities are empirically real in Hacking's sense. However, some aspects of Hacking's realism are to be criticized. Theoretical entities are to be resolved into the totality of the interrelated properties accessible to us by means of theoretical points of view embodied in scientific instruments. (shrink)

A number of philosophers have argued that a naturalized epistemology cannot be normative, and thus that the norms that govern science cannot themselves be established empirically. Three arguments for this conclusion are here developed and then responded to on behalf of naturalized epistemology. The response is developed in three stages. First, if we view human knowers as part of the natural world, then the attempt to establish epistemic norms that are immune to scientific evaluation faces difficulties that are at least (...) as severe as the purported difficulties for naturalized epistemology. Second, some examples of the ways in which norms are proposed and evaluated in the course of scientific research are considered and it is concluded that science has no need for trans?scientific norms. Finally, the three arguments introduced at the outset have no force when they are viewed in the light of the preceding discussion. (shrink)

Three major views of the observation?theory relation are now extant: (1) Observation and theory are mutually independent and observation provides the basis for evaluating theories. (2) Observations are theory?dependent and do not provide objective grounds for evaluating theories. (3) The concept of observation should be extended in a way that includes many so?called ?theoretical?entities? among the observables. Analyses of these views set the stage for a new approach that incorporates lessons learned from discussions of earlier accounts. The central idea of (...) this new approach is that empirical testing requires comparison of results arrived at by derivation from the theory being tested (plus appropriate auxiliary premises) with results derived from an interaction with aspects of nature in the theory's domain. These routes are independent in that each can be pursued without knowledge of the details or results of the alternative route. The approach accounts for the role of empirical results in evaluating theories without requiring that these results be theory?free or more certain than theoretical results. It also provides a basis for understanding the conditions under which a conflict between observation and theory can result in rejection of the observational result. (shrink)

Decision-making typically requires judgments about causal relations: we need to know the causal effects of our actions and the causal relevance of various environmental factors. We investigate how several individuals' causal judgments can be aggregated into collective causal judgments. First, we consider the aggregation of causal judgments via the aggregation of probabilistic judgments, and identify the limitations of this approach. We then explore the possibility of aggregating causal judgments independently of probabilistic ones. Formally, we introduce the problem of causal-network aggregation. (...) Finally, we revisit the aggregation of probabilistic judgments when this is constrained by prior aggregation of qualitative causal judgments. (shrink)

An important fact about human labor is that it can result not just in reproduction of what it started with, but in something new, a surplus product. When the latter is a means of production, it makes possible a mechanism of change consisting of reproduction by means of the expanded means of production. Each iteration of the labor process can differ from the preceding one insofar as it incorporates the surplus generated previously. Over the long-term, this cyclical process can lead (...) to the self-transformation of labor and, through it, of human societies and cultures. In this paper, I argue that this mechanism of change is also at work in the history of science. I argue that the form this mechanism takes in science is that of a feedback loop between discovery and instrument construction. This process requires the integration, and transformation into material form, of different kinds of knowledge. Based on this mechanism, I defend a concept of scientific progress as transcendence of the limitations of native human epistemic abilities. I also criticize narrowly biologistic approaches to the history of science for ignoring the role of surplus generation in transforming the labor process, and discuss some problems associated with viewing science as labor. (shrink)

The question of where, between theory and experiment, computer simulations (CSs) locate on the methodological map is one of the central questions in the epistemology of simulation (cf. Saam Journal for General Philosophy of Science, 48, 293–309, 2017). The two extremes on the map have them either be a kind of experiment in their own right (e.g. Barberousse et al. Synthese, 169, 557–574, 2009; Morgan 2002, 2003, Journal of Economic Methodology, 12(2), 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison (...) 2015; Massimi and Bhimji Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 51, 71–81, 2015; Parker Synthese, 169, 483–496, 2009) or just an argument executed with the aid of a computer (e.g. Beisbart European Journal for Philosophy of Science, 2, 395–434, 2012; Beisbart and Norton International Studies in the Philosophy of Science, 26, 403–422, 2012). There exist multiple versions of the first kind of position, whereas the latter is rather unified. I will argue that, while many claims about the ‘experimental’ status of CSs seem unjustified, there is a variant of the first position that seems preferable. In particular I will argue that while CSs respect the logic of (deductively valid) arguments, they neither agree with their pragmatics nor their epistemology. I will then lay out in what sense CSs can fruitfully be seen as experiments, and what features set them apart from traditional experiments nonetheless. I conclude that they should be seen as surrogate experiments, i.e. experiments executed consciously on the wrong kind of system, but with an exploitable connection to the system of interest. Finally, I contrast my view with that of Beisbart (European Journal for Philosophy of Science, 8, 171–204, 2018), according to which CSs are surrogates for experiments, arguing that this introduces an arbitrary split between CSs and other kinds of simulations. (shrink)

Scientists obtain a great deal of the evidence they use by observingnatural and experimentally generated objects and effects. Much of thestandard philosophical literature on this subject comes from20th century logical positivists and empiricists, theirfollowers, and critics who embraced their issues and accepted some oftheir assumptions even as they objected to specific views. Theirdiscussions of observational evidence tend to focus on epistemologicalquestions about its role in theory testing. This entry follows theirlead even though observational evidence also plays important andphilosophically interesting roles (...) in other areas including scientificdiscovery and the application of scientific theories to practicalproblems. (shrink)

Large scale experiments at CERN’s Large Hadron Collider rely heavily on computer simulations, a fact that has recently caught philosophers’ attention. CSs obviously require appropriate modeling, and it is a common assumption among philosophers that the relevant models can be ordered into hierarchical structures. Focusing on LHC’s ATLAS experiment, we will establish three central results here: with some distinct modifications, individual components of ATLAS’ overall simulation infrastructure can be ordered into hierarchical structures. Hence, to a good degree of approximation, hierarchical (...) accounts remain valid at least as descriptive accounts of initial modeling steps. In order to perform the epistemic function Winsberg Model-based reasoning in scientific discovery. Kluwer Academic/plenum Publishers, New York, pp 255–269, 1999) assigns to models in simulation—generate knowledge through a sequence of skillful but non-deductive transformations—ATLAS’ simulation models have to be considered part of a network rather than a hierarchy, in turn making the associated simulation modeling messy rather than motley. Deriving knowledge-claims from this ‘mess’ requires two sources of justification: holistic validation :253–262, 2010; in Carrier M, Nordmann A Science in the context of application. Springer, Berlin, pp 115–130, 2011), and model coherence. As it turns out, the degree of model coherence sets HEP apart from other messy, simulation-intensive disciplines such as climate science, and the reasons for this are to be sought in the historical, empirical and theoretical foundations of the respective discipline. (shrink)

Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue (...) that in a range of scientifically interesting cases they are particular abductions and defend this claim by appeal to two case studies. (shrink)

Ontic structural realism constitutes a promising take on scientific realism, one that avoids the well‐known issues that realist stances have with underdetermination and theory change. In its most radical versions, ontic structural realism proposes a type of eliminativism about theoretical entities, ascribing ontological commitment only to the structures, and not to the objects appearing in our theories. More moderate versions of ontic structural realism have also been proposed, allowing for ‘thin’ objects in the ontology. This work connects these takes on (...) structural realism with the independent notion that there are two categorically different kinds of scientific theories, namely those that deal with interactions and those that deal with structural constraints – what are known as interaction and framework theories, respectively. By taking this classification seriously, one can arrive at a selective version of ontic structural realism which is better adapted to our scientific knowledge, in which eliminativist ontic structural realism constitutes a natural fit to framework theories, whereas the moderate version is connected to interaction theories. (shrink)

What is the status of a cat in a virtual reality environment? Is it a real object? Or part of a fiction? Virtual realism, as defended by D. J. Chalmers, takes it to be a virtual object that really exists, that has properties and is involved in real events. His preferred specification of virtual realism identifies the cat with a digital object. The project of this paper is to use a comparison between virtual reality environments and scientific computer simulations to (...) critically engage with Chalmers’s position. I first argue that, if it is sound, his virtual realism should also be applied to objects that figure in scientific computer simulations, e.g. to simulated galaxies. This leads to a slippery slope because it implies an unreasonable proliferation of digital objects. A philosophical analysis of scientific computer simulations suggests an alternative picture: The cat and the galaxies are parts of fictional models for which the computer provides model descriptions. This result motivates a deeper analysis of the way in which Chalmers builds up his realism. I argue that he buys realism too cheap. For instance, he does not really specify what virtual objects are supposed to be. As a result, rhetoric aside, his virtual realism isn’t far from a sort of fictionalism. (shrink)

Computer simulations and experiments share many important features. One way of explaining the similarities is to say that computer simulations just are experiments. This claim is quite popular in the literature. The aim of this paper is to argue against the claim and to develop an alternative explanation of why computer simulations resemble experiments. To this purpose, experiment is characterized in terms of an intervention on a system and of the observation of the reaction. Thus, if computer simulations are experiments, (...) either the computer hardware or the target system must be intervened on and observed. I argue against the first option using the non-observation argument, among others. The second option is excluded by e.g. the over-control argument, which stresses epistemological differences between experiments and simulations. To account for the similarities between experiments and computer simulations, I propose to say that computer simulations can model possible experiments and do in fact often do so. (shrink)

A lot of attention has been devoted to the study of discoveries in high energy physics, but less on measurements aiming at improving an existing theory like the standard model of particle physics, getting more precise values for the parameters of the theory or establishing relationships between them. This paper provides a detailed and critical study of how measurements are performed in recent HEP experiments, taking examples from differential cross section measurements with the ATLAS detector at the LHC. This study (...) will be used to provide an elucidation of the concept of event used in HEP, in order to determine what constitutes an observation and what does not. It will highlight the essential place taken by theory-ladenness in order to produce observational facts, and will show how uncertainty and sensitivity estimates constitute an operational approach to robustness, inside the practice of science, avoiding potential circularity problem traditionally implied by theory-ladenness. This is in contrast to robustness analyses typically considered in the literature. A careful analysis of systematic uncertainty estimates and of statistical tests used to set empirical conclusions from the observations will however demonstrate that quantitative statements obtained from these statistical tests cannot be more than simple guiding arguments for the production of knowledge, but do not determine it. This indicates that the frontier between theory and observation is blurry and that the dichotomy theory-experiment should be revised. (shrink)

It is a widely shared view among philosophers of science that the theory-dependence (or theory-ladenness) of observations is worrying, because it can bias empirical tests in favour of the tested theories. These doubts are taken to be dispelled if an observation is influenced by a theory independent of the tested theory and thus circularity is avoided, while (partially) circular tests are taken to require special attention. Contrary to this consensus, it is argued that the epistemic value of theory-dependent tests has (...) nothing to do with the circularity or non-circularity of the test, but is instead based on the minimal empiricality and reliability of observations. Since theory-dependence does not in general prevent observations fulfilling these requirements, it should not be regarded as a phenomenon that is basically detrimental, but as neutral with respect to successful scientific knowledge gathering. (shrink)

Phenomenology has been adapted for use in qualitative health research, where it’s often used as a method for conducting interviews and analyzing interview data. But how can phenomenologists study subjects who cannot accurately reflect upon or report their own experiences, for instance, because of a psychiatric or neurological disorder? For conditions like these, qualitative researchers may gain more insight by conducting observational studies in lieu of, or in conjunction with, interviews. In this article, we introduce a phenomenological approach to conducting (...) this kind of observational research. The approach relies on conceptual grounding to focus a study on specific aspects of the participants’ experiences. Moreover, the approach maintains the openness to novel discoveries that qualitative research requires while also providing a structured framework for data collection and analysis. To illustrate its practical application, we use examples of hemispatial neglect—a neurologic disorder in which patients characteristically lack awareness of their own illness and bodily capacities. However, the approach that we describe can be applied more broadly to the study of complex illness experiences and other experiential alterations. (shrink)

The ontic conception of explanation is predicated on the proposition that “explanation is a relation between real objects in the world” and hence, according to this approach, scientific explanation cannot take place absent such a premise. Despite the fact that critics have emphasized several drawbacks of the ontic conception, as for example its inability to address the so-called “abstract explanations”, the debate is not settled and the ontic view can claim to capture cases of explanation that are non-abstract, such as (...) causal relations between events. However, by eliminating the distinction between abstract and non-abstract explanations, it follows that ontic and epistemic proposals can no longer contend to capture different cases of explanation and either all are captured by the ontic view or all are captured by the epistemic view. On closer inspection, it turns out that the ontic view deals with events that fall outside the scientists’ scope of observation and that it does not accommodate common instances of explanation such as explanations from false propositions and hence it cannot establish itself as the dominant philosophical stance with respect to explanation. On the contrary, the epistemic conception does account for almost all episodes of explanation and can be described as a relation between representations, whereby the explanans transmit information to the explanandum and that this information can come, dependent on context, in the form of any of the available theories of explanation (law-like, unificatory, causal and non-causal). The range of application of the ontic view thus is severely restricted to trivial cases of explanation that come through direct observation of the events involved in an explanation and explanation is to be mostly conceived epistemically. (shrink)

In The Uses of Argument, Stephen Toulmin proposed a model for the layout of arguments: claim, data, warrant, qualifier, rebuttal, backing. Since then, Toulmin’s model has been appropriated, adapted and extended by researchers in speech communications, philosophy and artificial intelligence. This book assembles the best contemporary reflection in these fields, extending or challenging Toulmin’s ideas in ways that make fresh contributions to the theory of analysing and evaluating arguments.

This volume is a collection of some of the most important philosophical papers by Peter Gärdenfors. Spanning a period of more than 20 years of his research, they cover a wide ground of topics, from early works on decision theory, belief revision and nonmonotonic logic to more recent work on conceptual spaces, inductive reasoning, semantics and the evolutions of thinking. Many of the papers have only been published in places that are difficult to access. The common theme of all the (...) papers is the dynamics of thought. Several of the papers have become minor classics and the volume bears witness of the wide scope of Gärdenfors’ research and of his crisp and often witty style of writing. The volume will be of interest to researchers in philosophy and other cognitive sciences. (shrink)

Despite the fact that reproduction of experiments by peers has traditionally been regarded as of the utmost importance in enabling the intersubjectivity of scientific practice, reproductions may yield discordant results and deciding which result should be favored may not be an easy task. According to Harry Collins, experimental disagreement is resolved by the action of social, political and economic factors, but not by means of epistemic and scientific, or so-called internal reasons. His motivation for such a claim is the presence (...) of an infinite regress at the core of experimental activity that, according to him, cannot be stopped with scientific resources alone: the experimenters’ regress. The goal of this... (shrink)

In this paper we argue that the difference between standard measurement and proxy measurement in paleoclimatology should not be understood in terms of ‘directness’. Measurements taken by climatologists to be paradigmatically non-proxy exhibit the kinds of indirectness that are thought to separate them proxy measurement. Rather, proxy measurements and standard measurements differ in how they account for confounding causal factors. Measurements are ‘proxy’ to the extent that the measurements require vicarious controls, while measurements are not proxy, but rather ‘standard’, to (...) the extent that the measurement apparatus provides sufficient physical control on its own. Guided by this account of proxy measurement, we then consider some of the challenges specific to historical proxy measurement and how it is that historical scientists address these challenges. Historical scientists rely on significant causal dependencies and naturally preserved signals to mitigate the influence of destructive processes over time. (shrink)

Neurath's proposal for the form of protocol statements explicates the multiple embedding of a singular sentence as specifying different conditions for the acceptance of such a sentence as a bona fide scientific datum. Before theories are accepted or rejected in the light of such evidence, however, a further condition must be met which Neurath did not formalize. The different conditions are discussed and shown to constitute a naturalistic theory of scientific data and a pragmatic theory of theory acceptance.

Charles Perrow used the term normal accidents to characterize a type of catastrophic failure that resulted when complex, tightly coupled production systems encountered a certain kind of anomalous event. These were events in which systems failures interacted with one another in a way that could not be anticipated, and could not be easily understood and corrected. Systems of the production of expert knowledge are increasingly becoming tightly coupled. Unlike classical science, which operated with a long time horizon, many current forms (...) of expert knowledge are directed at immediate solutions to complex problems. These are prone to breakdowns like the kind discussed by Perrow. The example of the Homestake mine experiment shows that even in modern physics complex systems can produce knowledge failures that last for decades. The concept of knowledge risk is introduced, and used to characterize the risk of failure in such systems of knowledge production. (shrink)

The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...) philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based. (shrink)

This article seeks rapprochement between the sociology of knowledge and philosophy of science by attempting to capture the best social constructionist insights within a strongly realistic philosophy of science. Key to doing so are separating the grounds for the individual scientist coming to know that P from those grounds for socially credentialing the claim that P within the relevant scientific subcommunity and showing how truth considerations can enter into the analysis of knowledge without interfering with social constructionist treatments of credentialing (...) claims. A detailed epistemology and associated account of the social credentialing of knowledge claims are presented. Close attention is paid to the epistemological and social aspects of the nature and role of observation reports, the interpretation of data, simplifications, idealizations, and approximations, and the nature of replication. The article contains a National Aeronautics and Space Administration remote-sensing case study and a detailed analysis of replication in the 1881–1933 Michelson-Morley-Miller interferometer ether studies. (shrink)

In april 1872, with the caisson at a depth of seventy-odd feet and still no bedrock, two men died. The strain for Roebling was nearly unbearable, as his wife later said. On May 18, a third man died, and that same day Roebling made the most difficult and courageous decision of the project. Staking everything — the success of the bridge, his reputation, his career - he ordered a halt. The New York tower, he had concluded, could stand where it (...) was, at a depth of 78 feet 6 inches, not on bedrock, but on “hardpack” sand. From examinations of the strata he had determined to his own satisfaction that no movement had occured at the level since the time of deposit millions of years in the geologic past; so, he said, it was “good enough to found upon”. (shrink)

There are various conceptions of objectivity, a characteristic of the scientific enterprise, the most fundamental being objectivity as faithfulness to facts. A brute fact, which happens independently from us, becomes a scientific fact once we take cognisance of it through the means made available to us by science. Because of the complex, reciprocal relationship between scientific facts and scientific theory, the concept of objectivity as faithfulness to facts does not hold in the strict sense of an aperspectival faithfulness to brute (...) facts. Nevertheless, it holds in the large sense of an underdetermined faithfulness to scientific facts, as long as we keep in mind the complexity of the notion of scientific fact (as theory-laden), and the role of non-factual elements in theory choice (as underdetermined by facts). Science remains our best way to separate our factual beliefs from our other kinds of beliefs. (shrink)

This paper examines the "causal theory of reference", according to which science aims at the discovery of "essences" which are the objects of reference of natural kind terms (among others). This theory has been advanced as an alternative to traditional views of "meaning", on which a number of philosophical accounts of science have relied, and which have been criticized earlier by the present author. However, this newer theory of reference is shown to be equally subject to fatal internal difficulties, and (...) to be incompatible with actual science as well. Indeed, it rests on assumptions which it shares with the purportedly opposing theory of meaning. Behind those common assumptions is the supposition that the nature of science can be illuminated by an examination of alleged necessities of language which are independent of the results and methods of scientific inquiry. An alternative view of science is proposed, according to which the goals and language of science develop as integral parts of the process of demarcating science from non-science, a process in which the notion of a "reason" gradually assumes a decisive role. On this view, the comparability, competition, and development of scientific ideas are understood without reliance on either common "meanings" or common "references" as fundamental tools of analysis. (shrink)

Jarrett Leplin has recently criticized a number of aspects of my views of the aims and goals of science, of the rationale of scientific change, and of the consequent relations between science and the philosophy of science, and in particular of the methodology of the latter (Leplin 1984, 1987, 1988a, 1988b). Here I will respond to those criticisms, and also reply to some related criticisms made by other writers.

The alleged problem of "incommensurability" is examined, and attempts to explain scientific change in terms of concepts of meaning and reference are analyzed and rejected. A way of understanding scientific change through a properly developed concept of "reasons" is presented, and the issues of reasons, meaning, and reference are placed in the context of this broader interpretation of scientific change.

The chief objections raised by Doppelt (this issue, "The Philosophical Requirements for an Adequate Conception of Scientific Rationality") against my views fall into three groups: ones having to do with my concept of "success" (that I have provided no analysis of it, and that therefore my concept of "reason" in science is likewise unexplained; that it requires appeal to some universal criterion); ones having to do with the role of standards or criteria in science (how they are related to substantive (...) beliefs; the possibility of rejecting them); and ones purporting to show that I have not escaped relativism (underdetermination of beliefs; problem of loss in scientific change). I reply to each of these groups of criticisms in turn, concluding with some remarks on the status and validity of the requirements he lays down for any account of scientific rationality. (shrink)

Relying on an analysis of the case of gravitational lensing, Hacking argues for a "modest antirealism" in astronomy. It is shown here that neither his scientific arguments nor his philosophical doctrines imply an antirealist conclusion. An alternative, realistic interpretation of gravitational lensing, and of the nature and history of astronomy more generally, is suggested.

Vision, Visibility, and Empirical Research. In general, natural scientists use the concept of observation in a liberal way: they talk of observing electrons, DNA, or distant quasars. Several philosophers of science have recently argued for a similar use of the concept of observation: they have claimed that the important aspects of scientific research can only be properly reconstructed in accordance with how this term is actually used in science. With reference to an example from astronomy, I point out that the (...) proposed generalisation of the concept of observation leads to undesirable consequences. I argue that a differentiated conceptual framework is required in order to give an adequate account of the varieties of scientific experience. Thus, the appropriate starting point for distinguishing these various scientific research practices should not be the generalised scientific conception of observation, but instead distinctly different uses of the term observation drawn from ordinary language. (shrink)

In the first part of my paper I discuss eight arguments in favour of the theory-dependence of observation: realistic content, guidance function of theories, perception as cognitive construction, expectation-dependence of perception, theory-dependence of scientific data, continuity between observational and theoretical concepts, language-dependence, and meaning holism. I argue that although these arguments make correct points, they do not exclude the existence of observations that are weakly theory-neutral in the sense that they don’t depend on acquired background knowledge. In the second part (...) I suggest an experimental method, the method of ostensive learning experiments, by which the degree of theory- and language-independence of a concept can be tested. (shrink)