Bayesians often assume, suppose, or conjecture that for any reasonable explication of the notion of simplicity a prior can be designed that will enforce a preference for hypotheses simpler in just that sense. But it is shown here that there are simplicity-driven approaches to curve-fitting problems that cannot be captured within the orthodox Bayesian framework.

Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...) into mathematical proofs which drop out before the solution. Or better, they are like the hypotheses that drive science, which do not themselves need to be true. In other words, it does not matter whether or not intuitions are accurate as descriptions of the natural kinds that undergird philosophical concepts; the aims of conceptual analysis can still be met. (shrink)

Philosophers of science turned to historical case studies in part in response to Thomas Kuhn's insistence that such studies can transform the philosophy of science. In this issue Joseph Pitt argues that the power of case studies to instruct us about scientific methodology and epistemology depends on prior philosophical commitments, without which case studies are not philosophically useful. Here I reply to Pitt, demonstrating that case studies, properly deployed, illustrate styles of scientific work and modes of argumentation that are not (...) well handled by currently standard philosophical analyses. I illustrate these claims with exemplary findings from case studies dealing with exploratory experimentation and with interdisciplinary cooperation across sciences to yield multiple independent means of access to theoretical entities. The latter cases provide examples of ways that scientists support claims about theoretical entities that are not available in work performed within a single discipline. They also illustrate means of correcting systematic biases that stem from the commitments of each discipline taken separately. These findings illustrate the transformative power of case study methods, allow us to escape from the horns of Pitt's "dilemma of case studies," and vindicate some of the post-Kuhn uses to which case studies have been put. (shrink)

H. B. D. Kettlewell's (1955, 1956) classic field experiments on industrial melanism in polluted and unpolluted settings using the peppered moth, Biston betularia, are routinely cited as establishing that the melanic (dark) form of the moth rose in frequency downwind of industrial centers because of the cryptic advantage dark coloration provides against visual predators in soot-darkened environments. This paper critiques three common myths surrounding these investigations: (1) that Kettlewell used a model that identified crypsis as the only selective force responsible (...) for the spread of the melanic gene, (2) that Kettlewell's field experiments alone established that selection for crypsis was the most important factor in the spread of melanic forms, and (3) that Kettlewell's investigations in an unpolluted wood near Dorset constituted a control for his earlier Birmingham studies (contra Hagen 1993, 1996). This analysis further identifies two features that distinguish manipulative experiments in evolutionary biology from experiments in other contexts. First, experiments in evolutionary biology rest on a wealth of information provided by strictly observational ecological studies; in the absence of such information experiments in evolutionary biology make no sense. Second, there is a trade-off between how much control investigators have over the conditions being studied and how informative the results of the experiment will be with regard to natural populations. (shrink)

Laudan famously argued that neither truth nor approximate truth can be part of an explanation of a scientific theory's predictive success because in the history of science there were theories that enjoyed some limited success but now are considered outright false. The power of his argument lay in the many historic examples he listed . Realists have disputed that all theories on Laudan's list can be regarded as predictively successful but let's suppose momentarily that at least some exist that support (...) his point. In this case, there are historic false theories that made some true predictions. We are aiming for a general explanation of a theory's predictive success and hence these false theories necessarily are on board. Now, Laudan also argues that historic false theories – the downright false ones and the ones we nowadays judge as strictly false, but approximately true – do not in any principled sense differ from the ones we presently accept. These theories seem to present a good basis for inductively inferring that any presently accepted scientific theory is actually false. Many presently accepted theories certainly are predictively successful to a great extent and certainly their success should be covered by an acceptable explanation. Since there seems to be inductive support for the conclusion that …. (shrink)

It is customary to distinguish experimental from purely observational sciences. The former include physics and molecular biology, the latter astronomy and palaeontology. Experiments involve actively intervening in the course of nature, as opposed to observing events that would have happened anyway. When a molecular biologist inserts viral DNA into a bacterium in his laboratory, this is an experiment; but when an astronomer points his telescope at the heavens, this is an observation. Without the biologist’s handiwork the bacterium would never have (...) contained foreign DNA; but the planets would have continued orbiting the sun whether or not the astronomer had directed his telescope skyward. The observational/experimental distinction would probably be difficult to make precise 1, as the notion of an ‘intervention’ is not easily defined, but it is intuitively fairly clear, and is frequently invoked by scientists and historians of science. Experimentation, or ‘putting questions to nature’, is often cited as a hallmark of the modern scientific method, something that permitted the enormous advances of the last 350 years. And it is sometimes said that the social sciences lag behind the natural because controlled experiments cannot be done so readily in the former. Moreover in certain sciences, e.g. epidemiology, students are explicitly taught that experimental data is preferable to observational data, particularly for doing causal inference. So the distinction between observational and experimental science has quite wide currency, and is often regarded as methodologically significant. Surprisingly, mainstream philosophy of science has had rather little to say about the observational/experimental distinction. 2 For example, discussions of confirmation usually invoke a notion of ‘evidence’, to be contrasted with ‘theory’ or ‘hypothesis’; the aim is to understand how the evidence bears on the hypothesis. But whether this ‘evidence’ comes from observation or experiment generally plays no role in the discussion; this is true …. (shrink)

In this paper I argue that aim-oriented empiricism (AOE), a conception of natural science that I have defended at some length elsewhere[1], is a kind of synthesis of the views of Popper, Kuhn and Lakatos, but is also an improvement over the views of all three. Whereas Popper's falsificationism protects metaphysical assumptions implicitly made by science from criticism, AOE exposes all such assumptions to sustained criticism, and furthermore focuses criticism on those assumptions most likely to need revision if science is (...) to make progress. Even though AOE is, in this way, more Popperian than Popper, it is also, in some respects, more like the views of Kuhn and Lakatos than falsificationism is. AOE is able, however, to solve problems which Kuhn's and Lakatos's views cannot solve. [Back to Top]. (shrink)

Karl Popper is famous for having proposed that science advances by a process of conjecture and refutation. He is also famous for defending the open society against what he saw as its arch enemies – Plato and Marx. Popper’s contributions to thought are of profound importance, but they are not the last word on the subject. They need to be improved. My concern in this book is to spell out what is of greatest importance in Popper’s work, what its failings (...) are, how it needs to be improved to overcome these failings, and what implications emerge as a result. The book consists of a collection of essays which dramatically develop Karl Popper’s views about natural and social science, and how we should go about trying to solve social problems. Criticism of Popper’s falsificationist philosophy of natural science leads to a conception of science that I call aim-oriented empiricism. This makes explicit metaphysical theses concerning the comprehensibility and knowability of the universe that are an implicit part of scientific knowledge – implicit in the way science excludes all theories that are not explanatory, even those that are more successful empirically than accepted theories. Aim-oriented empiricism has major implications, not just for the academic discipline of philosophy of science, but for science itself. Popper generalized his philosophy of science of falsificationism to arrive at a new conception of rationality – critical rationalism – the key methodological idea of Popper’s profound critical exploration of political and social issues in his The Open Society and Its Enemies, and The Poverty of Historicism. This path of Popper, from scientific method to rationality and social and political issues is followed here, but the starting point is aim-oriented empiricism rather than falsificationism. Aim-oriented empiricism is generalized to form a conception of rationality I call aim-oriented rationalism. This has far-reaching implications for political and social issues, for the nature of social inquiry and the humanities, and indeed for academic inquiry as a whole. The strategies for tackling social problems that arise from aim-oriented rationalism improve on Popper’s recommended strategies of piecemeal social engineering and critical rationalism, associated with Popper’s conception of the open society. This book thus sets out to develop Popper’s philosophy in new and fruitful directions. The theme of the book, in short, is to discover what can be learned from scientific progress about how to achieve social progress towards a better world. (shrink)

(i) Scientific realism is primarily a metaphysical doctrine about the existence and nature of the unobservables of science. (ii) There are good explanationist arguments for realism, most famously that from the success of science, provided abduction is allowed. Abduction seems to be on an equal footing, at least, with other ampliative methods of inference. (iii) We have no reason to believe a doctrine of empirical equivalence that would sustain the underdetermination argument against realism. (iv) The key to defending realism from (...) the pessimistic meta-induction is that we have greatly improved our capacity to understand the unobservable world over recent centuries. (shrink)

Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...) in philosophy of science drew attention to the fact that many experimental phenomena have a ‘life of their own’: the conviction that they are real is not dependent on the theories used to characterise and explain them. I suggest that something similar can be true of descriptive phenomena, and that many homologies are phenomena of this kind. As a result the descriptive biology of form and function has a life of its own—a degree of epistemological independence from the theories that explain form and function. I also suggest that the two major ‘homology concepts’ in contemporary biology, usually seen as two competing definitions, are in reality complementary elements of the biological explanation of homology. (shrink)

: Bayesians and error statisticians have relied heavily upon examples from physics in developing their accounts of scientific inference. The present essay demonstrates it is possible to analyze H.B.D. Kettlewell's classic study of natural selection from Deborah Mayo's error statistical point of view (Mayo 1996). A comparison with a previous analysis of this episode from a Bayesian perspective (Rudge 1998) reveals that the error statistical account makes better sense of investigations such as Kettlewell's because it clarifies how core elements in (...) the design of experiments are used to minimize erroneous inferences rather than dwelling on whether the strategies used are reasonable. (shrink)

: Where there are cases of underdetermination in scientific controversies, such as the case of the molecular clock, scientists may direct the course and terms of dispute by playing off the multidimensional framework of theory evaluation. This is because assessment strategies themselves are underdetermined. Within the framework of assessment, there are a variety of trade-offs between different strategies as well as shifting emphases as specific strategies are given more or less weight in assessment situations. When a strategy is underdetermined, scientists (...) can change the dynamics of a controversy by making assessments using different combinations of evaluation strategies and/or weighting whatever strategies are in play in different ways. Following an underdetermination strategy does not end or resolve a scientific dispute. Consequently, manipulating underdetermination is a feature of controversy dynamics and not controversy closure. (shrink)

In the 1950s–60s biochemists searched intensively for a series of high-energy molecules in the cell. Although we now believe that these molecules do not exist, biochemists claimed to have isolated or identified them on at least sixteen occasions. The episode parallels the familiar eighteenth-century case of phlogiston, in illustrating how error is not simply the loss of facts but, instead, must be actively constructed. In addition, the debates surrounding each case demonstrate how revolutionary-scale disagreement is sometimes resolved by differentiating or (...) partitioning empirical domains, rather than by replacement of one theory by another. (shrink)

Bayesian confirmation theory is our best formal framework for describing inductive reasoning. The problem of old evidence is a particularly difficult one for confirmation theory, because it suggests that this framework fails to account for central and important cases of inductive reasoning and scientific inference. I show that we can appeal to the fragmentation of doxastic states to solve this problem for confirmation theory. This fragmentation solution is independently well-motivated because of the success of fragmentation in solving other problems. I (...) also argue that the fragmentation solution is preferable to other solutions to the problem of old evidence. These other solutions are already committed to something like fragmentation, but suffer from difficulties due to their additional commitments. If these arguments are successful, Bayesian confirmation theory is saved from the problem of old evidence, and the argument for fragmentation is bolstered by its ability to solve yet another problem. (shrink)

Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively (...) as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (shrink)

In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper de?nition and (...) that its bearing on the question of whether a proposition is true is highly problematic” (533). Replies to Orzack and Sober, from Levins (1993) and Weisberg (2006b), have rejected the idea that RA, on its own, can con?rm the results of models. I argue that these replies have not properly addressed Orzack and Sober’s real criticisms, which focus not on the role of empirical data in RA but on the problem of ensuring that the models used in RA are independent. By drawing on accounts of RA in experimental science, I argue that there is in fact a fallible but viable form of RA that can both con?rm the results of models and incorporate empirical data. However, for reasons other than those of Orzack and Sober, I conclude that RA may be of limited use in model-based science, as the example of ?shery biology can show. (shrink)

Today, mechanisms and mechanistic explanation are very popular in philosophy of science and are deemed a welcome alternative to laws of nature and deductive‐nomological explanation. Starting from Mitchell's pragmatic notion of laws, I cast doubt on their status as a genuine alternative. I argue that (1) all complex‐systems mechanisms ontologically must rely on stable regularities, while (2) the reverse need not hold. Analogously, (3) models of mechanisms must incorporate pragmatic laws, while (4) such laws themselves need not always refer to (...) underlying mechanisms. Finally, I show that Mitchell's account is more encompassing than the mechanistic account *Received August 2008; revised January 2010. †To contact the author, please write to: Centre for Logic and Philosophy of Science, Ghent University, Blandijnberg 2, B‐9000 Belgium; e‐mail: [email protected]. (shrink)

I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.

Any advanced theory of physics contains modules defined as essential components that are themselves theories with different domains of application. Different kinds of modules can be distinguished according to the way in which they fit in the symbolic and interpretive apparatus of a theory. The number and kind of the modules of a given theory vary as the theory evolves in time. The relative stability of modules and the variability of their insertion in other theories play a vital role in (...) the application, comparison, construction, and communication of theories. Modularity conveys some global unity to physics through the sharing of modules by diverse theories. This alternative to rigid hierarchies and holistic totalities permits a dynamical, plastic, and symbiotic approach to physical theory. (shrink)

This paper deals with the following question: What features of modern natural science are responsible for the fact that, of all forms of science, this form is technologically exploitable? The three notions: concept of nature, epistemic ideal, and experiment, suggest the most important components of my answer. I will argue, first, that only the peculiar interplay of the modern concept of nature with an epistemic ideal attuned to it can cast experiment in the specific, highly central role it plays in (...) the pursuit of knowledge about nature. It will then become clear that the form of science in which experiment plays such a role will, necessarily, prove technologically exploitable. (shrink)

Effective field theories have been a very popular tool in quantum physics for almost two decades. And there are good reasons for this. I will argue that effective field theories share many of the advantages of both fundamental theories and phenomenological models, while avoiding their respective shortcomings. They are, for example, flexible enough to cover a wide range of phenomena, and concrete enough to provide a detailed story of the specific mechanisms at work at a given energy scale. So will (...) all of physics eventually converge on effective field theories? This paper argues that good scientific research can be characterised by a fruitful interaction between fundamental theories, phenomenological models and effective field theories. All of them have their appropriate functions in the research process, and all of them are indispensable. They complement each other and hang together in a coherent way which I shall characterise in some detail. To illustrate all this I will present a case study from nuclear and particle physics. The resulting view about scientific theorising is inherently pluralistic, and has implications for the debates about reductionism and scientific explanation. (shrink)

Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments or simulations, (...) per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive. (shrink)

This paper takes part in the methodological debate concerning the nature and the justification of hypotheses about computational systems in software engineering by providing an epistemological analysis of Software Testing, the practice of observing the programs’ executions to examine whether they fulfil software requirements. Property specifications articulating such requirements are shown to involve falsifiable hypotheses about software systems that are evaluated by means of tests which are likely to falsify those hypotheses. Software Reliability metrics, used to measure the growth of (...) probability that given failures will occur at specified times as new executions are observed, is shown to involve a Bayesian confirmation of falsifiable hypotheses on programs. Coverage criteria, used to select those input values with which the system under test is to be launched, are understood as theory-laden principles guiding software tests, here compared to scientific experiments. Redundant computations, fault seeding models and formal methods used in software engineering to evaluate test results are taken to be instantiations of some epistemological strategies used in scientific experiments to distinguish between valid and non-valid experimental outcomes. The final part of the paper explores the problem, advanced in the context of the philosophy of technology, of defining the epistemological status of software engineering by conceiving it as a scientifically attested technology. (shrink)

In this chapter I investigate the prospects of integrated history and philosophy of science, by examining how philosophical issues raised by “hidden entities”, entities that are not accessible to unmediated observation, can enrich the historical investigation of their careers. Conversely, I suggest that the history of those entities has important lessons to teach to the philosophy of science. Hidden entities have played a crucial role in the development of the natural sciences. Despite their centrality to past scientific practice, however, several (...) of them (e.g., phlogiston, caloric, and the ether) turned out to be fictitious. For this reason, they have figured prominently in recent debates on scientific realism. The issues I explore in this paper are entangled with those debates. I argue that our understanding of hidden entities and their role in experimental practice can be enhanced by adopting an integrated historical-cum-philosophical approach. On the one hand, philosophical reflection on the reality of those entities has a lot to gain by examining historically how they were ntroduced and investigated. On the other hand, the historical reconstruction of the careers of those entities may profit from philosophical reflection on their existence. (shrink)

H. Collins has challenged the empiricist understanding of experimentation by identifying what he thinks constitutes the experimenter’s regress: an instrument is deemed good because it produces good results, and vice versa. The calibration of an instrument cannot alone validate the results: the regressive circling is broken by an agreement essentially external to experimental procedures. In response, A. Franklin has argued that calibration is a key reasonable strategy physicists use to validate production of results independently of their interpretation. The physicists’ arguments (...) about the merits of calibration are not coextensive with the interpretation of results, and thus an objective validation of results is possible. I argue, however, that the in-situ calibrating and measurement procedures and parameters at the Large Hadron Collider are closely and systematically interrelated. This requires empiricists to question their insistence on the independence of calibration from the outcomes of the experiment and rethink their position. Yet this does not leave the case of in-situ calibration open to the experimenter’s regress argument; it is predicated on too crude a view of the relationship between calibration and measurement that fails to capture crucial subtleties of the case. (shrink)

The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better understanding of the idiosyncrasies, which (...) manifest in terms of a nonstandard role for experimentation, are interesting both for computer scientists and for philosophers of science. Computer scientists can think more clearly about their experimental choices. The role of experimentation elucidated by computer science merits further study from philosophers of science generally, as it highlights a role for experimentation hitherto unrecognized by philosophers: demonstration that activities exist. (shrink)

ArgumentIn the theory-dominated view of scientific experimentation, all relations of theory and experiment are taken on a par; namely, that experiments are performed solely to ascertain the conclusions of scientific theories. As a result, different aspects of experimentation and of the relations of theory to experiment remain undifferentiated. This in turn fosters a notion of theory-ladenness of experimentation (TLE) that is toocoarse-grainedto accurately describe the relations of theory and experiment in scientific practice. By contrast, in this article, I suggest that (...) TLE should be understood as anumbrella conceptthat has different senses. To this end, I introduce a three-fold distinction among the theories of high-energy particle physics (HEP) as background theories, model theories, and phenomenological models. Drawing on this categorization, I contrast two types of experimentation, namely, “theory-driven” and “exploratory” experiments, and I distinguish between the “weak” and “strong” senses of TLE in the context of scattering experiments from the history of HEP. This distinction enables identifying the exploratory character of the deep-inelastic electron-proton scattering experiments – performed at the Stanford Linear Accelerator Center (SLAC) between the years 1967 and 1973 – thereby shedding light on a crucial phase of the history of HEP, namely, the discovery of “scaling,” which was the decisive step towards the construction of quantum chromo-dynamics as a gauge theory of strong interactions. (shrink)

: This paper explores the calibration of laboratory models in population genetics as an experimental strategy for justifying experimental results and claims based upon them following Franklin (1986, 1990) and Rudge (1996, 1998). The analysis provided undermines Coyne et al.'s (1997) critique of Wade and Goodnight's (1991) experimental study of Wright's (1931, 1932) Shifting Balance Theory. The essay concludes by further demonstrating how this analysis bears on Diamond's (1986) claims regarding the weakness of laboratory experiments as evidence, and further how (...) the calibration strategy fits within Lloyd's (1987, 1988) account of the confirmation of ecological and evolutionary models. (shrink)

Despite its potential implications for the objectivity of scientific knowledge, the claim that “scientific instruments are perspectival” has received little critical attention. I show that this claim is best understood as highlighting the dependence of instruments on different perspectives. When closely analyzed, instead of constituting a novel epistemic challenge, this dependence can be exploited to mount novel strategies for resolving two old epistemic problems: conceptual relativism and theory-ladeness. The novel content of this article consists in articulating and developing these strategies (...) by introducing two fine-grained notions of perspectives as the key units of analysis: “broad perspectives” and “narrow perspectives.”. (shrink)

The thesis consists of an introduction and five papers. The introduction gives a brief historical survey of empirical investigations into the effectiveness of medicinal interventions, as well as surveys of the concept of evidence and of the history and philosophy of experiments. The main ideas of the EBM movement are also presented. Paper I: Concerns have been raised that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualised treatments, for example traditional homeopathy. (...) With respect to individualised treatments, it is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of treatment groups and the elimination of confounding variables or variations. These conditions do not preclude the testing of individualised medicine. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in the EBM literature. When discussed, mechanistic reasoning has almost exclusively been positive – both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Paper III: Evidence hierarchies are lists of investigative strategies ordered with regard to the claimed strength of evidence. They have been used for a couple of decades within EBM, particularly for the assessment of evidence for treatment recommendations, but they remain controversial. An under-investigated question is what the order in the hierarchy means. Four interpretations of the order are distinguished and discussed. The two most credible ones are, in rough terms, “typically stronger” and “ideally stronger”. The GRADE framework seems to be based on the “typically stronger” reading. Even if the interpretation of an evidence hierarchy were established, hierarchies appear to be rather unhelpful for the task of evidence aggregation. However, specifying the intended order relation may help sort out disagreements. Paper IV: There are three main arguments for randomisation that connect inseparably to theoretical concepts: Randomisation is useful for performing null hypothesis testing. Randomisation is needed for plausible causal inferences from treatment to effect. Randomisation is acceptable and computationally convenient in a Bayesian setting. A critical scrutiny of these arguments shows that is acceptable in the context of clinical trials. As for, it is argued that randomisation only provides weak reasons for drawing causal inferences in the context of real clinical trials. Argument is weak because it is controversial among Bayesians, and because formally Bayesian analyses of trial results are rarely asked for. Paper V: Practical arguments for randomisation are arguments with no necessary connections to theoretical frameworks like null hypothesis testing or causal inferences. Four common practical arguments in the context of clinical trials are distinguished and assessed: Randomisation contributes to allocation concealment. Randomisation contributes to the baseline balance of treatment groups. Randomisation decreases self-selection bias. Randomisation removes allocation bias. Argument is rejected. Arguments and are approved. Argument is rejected if it is formulated so as to be independent from and, but it is true that randomisation contributes to balance through the mechanisms mentioned in and. It is judged that may be the strongest single argument. (shrink)

IntroductionThe aim of this paper is to outline the program of a hermeneutic theory of the way in which reality becomes disclosed and meaningfully articulated in practices of scientific inquiry.Text and MethodsI describe the profile of hermeneutic realism by addressing the issue of how objectified factuality is produced within the facticity of inquiry. Hermeneutic realism is characterized as a position that discards foundational epistemology and cognitive essentialism. I argue that the meaningful articulation of domains disclosed in scientific inquiry is an (...) ontologically self-sufficient process. This claim is the kernel of interpretive internalism. At stake in my analysis is the interplay of interrelated scientific practices and the possibilities for doing research, granted that the practices’ interrelatedness is projected upon the horizon of possibilities. Three kinds of hermeneutic circularity in this interplay are distinguished. They refer accordingly to the selection of data, the construction of data-models, and the saving of phenomena whereby theoretical objects become contextually envisioned. The main emphasis is placed on the reading of theoretical objects in the articulation of scientific domains.ConclusionThus, the kind of philosophy of science pertinent to hermeneutic realism and interpretive internalism aims at revealing reality within the facticity of inquiry. (shrink)

The roles of classical realism, logical positivism, and pragmatic instrumentalism in the shaping of fundamental ideas in quantum physics are examined in the light of some recent historical and sociological studies of the factors that influenced their development. It is shown that those studies indicate that the conventionalistic form of instrumentalism that has dominated all the major post-World War II developments in quantum physics is not an outgrowth of the Copenhagen school, and that despite the “schism” in twentieth century physics (...) created by the Bohr-Einstein “disagreements” on foundational issues in quantum theory, both their philosophical stands were very much opposed to those of conventionalistic instrumentalism. Quotations from the writings of Dirac, Heisenberg, Popper, Russell, and other influential thinkers, are provided, illustrating the fact that, despite the various divergencies in their opinions, they all either opposed the instrumentalist concept of “truth” in general, or its conventionalistic version in post-World War II quantum physics in particular. The basic epistemic ideas of a quantum geometry approach to quantum physics are reviewed and discussed from the point of view of a quantum realism that seeks to reconcile Bohr's “positivism” with Einstein's “realism” by emphasizing the existence of an underlying quantum reality, in which they both believed. This quantum geometry framework seeks to introduce geometro-stochastic concepts that are specifically designed for the systematic description of that underlying quantum reality, by developing the conceptual and mathematical tools that are most appropriate for such a use. (shrink)

The past quarter century has seen an enormous growth of interest among scholars of science and technology in both particular experimental episodes and the process of experimentation. Among the most influential accounts have been those developed by Allan Franklin (1986, 1990), Deborah Mayo (1996) and Peter Galison (1987), each of which was developed primarily with reference to examples drawn from the history of physics. One useful way to access the generality of an account of experiment is to see how it (...) fares with reference to examples drawn from disciplines far removed from the context within which it was developed. In previous essays I examined and compared the adequacy of Franklin and Mayo’s views on experiment with reference to an episode drawn from the history of evolutionary biology, H.B.D. Kettlewell's classic studies of the phenomenon of industrial melanism (Rudge 1998, 2001). The present essay reanalyzes Kettlewell’s work once more, this time as a test of Peter Galison’s provocative account of experimentation in the sciences. Kettlewell’s investigations can indeed be interpreted within Galison’s perspective, but this appears to reflect the vagueness of many key distinctions Galison makes more than any special insights his views provide on the nature of experimentation in evolutionary biology. (shrink)

Psychological research has shown that cognitive illusions, of which visual illusions are just a special case, are systematic and pervasive, raising epistemological questions about how error in all forms of research can be identified and eliminated. The quantitative sciences make use of statistical techniques for this purpose, but it is not clear what the qualitative equivalent is, particularly in view of widespread scepticism about validity and objectivity. I argue that, in the light of cognitive psychology, the ‘error question’ cannot be (...) dismissed as a positivist obsession, and that the concepts of truth and objectivity are unavoidable. However, they constitute only a ‘minimal realism’, which does not necessarily bring a commitment to ‘absolute’ truth, certainty, correspondence, causation, reductionism, or universal laws in its wake. The assumption that it does reflects a misreading of positivism and, ironically, precipitates a ‘crisis of legitimation and representation’, as described by constructivist authors. (shrink)

In recent years there has been a revival of the debate about the relation between history and philosophy of science. This article seeks to contribute to the discussion by approaching the issue from a new angle. To rethink the relation between the two domains of study, I apply an important insight about scientific practice to the practice of integrating the history and philosophy of science: the insight that the scientific paper does not give a faithful account of the actual research (...) pursued in the laboratory or in the field. Arguably, the scholarly article about science is also not a transparent window to the activity of producing such an article. But if it is not, we need to redirect our attention. If we want to understand the nature and merits of integrating the history and philosophy of science, we need to examine both the actual activity of integrating and the scholarly paper produced by it. To consider what one can learn from such an inquiry, I reflect on my own activity of studying scientific justification through the combination of historical and philosophical analysis. Probing a concrete historical episode, micro-anatomical research on the retina in the 19th century, I pursue two related questions, the first-order question, 'What exactly is scientific justification in the given case?' and the meta-question, 'How do I go about analysing justificatory practices?' I then characterise the nature of my analysis and consider what can be learned from the study of the practice of integrating the history and philosophy of science. (shrink)

The aim of this paper is to discuss a key question in the history and philosophy of medicine, namely how scholars should treat the practices and experimental hypotheses of modern life science laboratories. The paper seeks to introduce some prominent historiographical methods and theoretical approaches associated with biomedical research. Although medical scientists need no convincing that experimentation has a significant function in their laboratory work, historians, philosophers, and sociologists long neglected its importance when examining changes in medical theories or progress (...) in scientific knowledge. The reason appears to have been the academic influence of the then dominant tradition in the history of ideas, but was also due to a misconception of what could usefully be termed the view on “historical ontology.” During the last two decades, there have been many books and research articles that have turned towards the subject, so that the study of experimental practice has become a major trend in the contemporary history and philosophy of medicine. A closer look at the issue of laboratory research shows that concepts in medicine and the life sciences cannot be understood as historically constant, free-standing ideas, but have to be regarded as dependent on local research settings. They often carry particular “social memories” with them and thus acquire important ethical implications. (shrink)

We employ data envelopment analysis on a series of experiments performed in Fermilab, one of the major high-energy physics laboratories in the world, in order to test their efficiency (as measured by publication and citation rates) in terms of variations of team size, number of teams per experiment, and completion time. We present the results and analyze them, focusing in particular on inherent connections between quantitative team composition and diversity, and discuss them in relation to other factors contributing to scientific (...) production in a wider sense. Our results concur with the results of other studies across the sciences showing that smaller research teams are more productive, and with the conjecture on curvilinear dependence of team size and efficiency. (shrink)

Prediction is more than testing established theory by examining whether the prediction matches the data. To show this, I examine the practices of a community of scientists, known as threaders, who are attempting to predict the final, folded structure of a protein from its primary structure, i.e., its amino acid sequence. These scientists employ a careful and deliberate methodology of prediction. A key feature of the methodology is calibration. They calibrate in order to construct better models. The construction leads to (...) knowledge of how to construct or build an object. Thus, prediction serves a cognitive goal of model construction and not just model or theory testing. The kind of knowledge that results is relevantly different than theoretical knowledge. (shrink)

This paper deals with calibration in scientific practices which investigate relatively well-understood natural phenomena by means of already standardized instrumental devices. Calibration is a crucial topic, since it conditions the reliability of instrumental procedures in science. Yet although important, calibration is a relatively neglected topic. We think more attention should be devoted to calibration. The paper attempts to take a step in this direction. The aims are two-fold: (1) to characterize calibration in a relatively simple kind of scientific practices; (2) (...) to provide conceptual and taxonomic tools of broader scope that help to get a better understanding of calibration in more complex cases and other kinds of scientific practices. For this purpose, we first provide indications for why a conceptual framework is needed. Second, a bibliographic survey of works dealing with calibration is attempted. Third, we introduce different tools to enable a better understanding of calibration. Fourth, we turn to the elaboration of what we call a “simple exemplar” of calibration, illustrated through the case of the calibration of an equal-arm balance. Fifth, the tools previously introduced, and the framework of the simple exemplar, are applied to a more complex case of calibration: calibration procedures in X-ray experiments. This serves to show the work accomplished by the simple exemplar and to emphasize features of more complex cases of calibration. Eventually, we revisit and specify the nature, status, scope and value of the proposed framework. (shrink)

The foundational difficulties encountered by the conventional formulation of quantum electrodynamics, and the criticism by Dirac, Schwinger, Rohrlich, and others, aimed at some of the physical and mathematical premises underlying that formulation, are reviewed and discussed. The basic failings of the conventional methods of quantization of the electromagnetic field are pointed out, especially with regard to the issue of local (anti)commutativity of quantum fields as an embodiment of relativistic microcausality. A brief description is given of a recently advanced new type (...) of approach to quantum electrodynamics, and to quantum field theory in general, which is epistemically based on intrinsically quantum ideas about the physical nature of spacetime, and is mathematically based on a fiber theoretical formulation of quantum geometries, aimed in part at removing the aforementioned difficulties and inconsistencies. It is shown that these ideas can be traced to a conceptualization of spacetime outlined by Einstein in the last edition of his well-known semipopular exposition of relativity theory. (shrink)

Psychological research has shown that cognitive illusions, of which visual illusions are just a special case, are systematic and pervasive, raising epistemological questions about how error in all forms of research can be identified and eliminated. The quantitative sciences make use of statistical techniques for this purpose, but it is not clear what the qualitative equivalent is, particularly in view of widespread scepticism about validity and objectivity. I argue that, in the light of cognitive psychology, the ‘error question’ cannot be (...) dismissed as a positivist obsession, and that the concepts of truth and objectivity are unavoidable. However, they constitute only a ‘minimal realism’, which does not necessarily bring a commitment to ‘absolute’ truth, certainty, correspondence, causation, reductionism, or universal laws in its wake. The assumption that it does reflects a misreading of positivism and, ironically, precipitates a ‘crisis of legitimation and representation’, as described by constructivist authors. (shrink)

The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...) the representational adequacy of qualitative models is essential to evaluate reachability properties. Justification theory, if not playing an essential role in EOCS, is exhibited to be involved in the process of advancing and corroborating model-based hypotheses about empirical systems in ECB and ABM. Finally, the practice of evaluating model-based hypothesis by testing the simulated systems is shown to constitute an argument in favour of the thesis that computer simulations in ECB and ABM can be put on a par with scientific experiments. (shrink)