Theoretical Virtues

I review and challenge the views on simplicity and its role in linguistics put forward by Ludlow. In particular, I criticize the claim that simplicity—in the sense pertinent to science—is nothing more than ease of use or “user-friendliness”, motivated by economy of labor. I argue that Ludlow’s discussion fails to do justice to the diversity of factors that are relevant to simplicity considerations. This, in turn, leads to the neglect of crucial cases in which the rationale for simplification is unmistakably (...) epistemic, as well as instances where simplicity is part of the content of substantive, empirical hypotheses. I illustrate these points with examples from the history of generative linguistics, such as: the shaping influence exerted by simplicity, via its involvement in the notion of “linguistically significant generalization”, its methodological and substantive contribution to the goal of explanatory adequacy, and its central role in the Minimalist Program’s search “beyond explanatory adequacy”. (shrink)

Galileo’s telescopic lunar observations, announced in Siderius Nuncius (1610), were a triumph of observational skill and ingenuity. Yet, unlike the Medicean stars, Galileo’s lunar “discoveries” were not especially novel. Indeed, Plutarch had noted the moon’s uneven surface in classical times, and many other renaissance observers had also turned their gaze moonward, even (in Harriot’s case) aided by telescopes of their own. Moreover, what Galileo and his contemporaries saw was colored by the assumptions they already had. Copernicans assumed the moon was (...) a terrestrial satellite, thus Galileo saw its mountains and Kepler “saw” the dwellings of its inhabitants. Aristotelians assumed the moon was a perfect sphere, so they saw differences in density and rarity in the lunar body. Theory corrected the results of observation, so Galileo’s lunar observations, like those that had come before, proved nothing. Yet this failure contained the germ of Galileo’s success, since the Siderius Nuncius gave observation a rhetorical force it did not have before. Observers on all sides set out to see for themselves what Galileo reported. Hence, all parties now had to answer to what they saw, whatever they believed. Thus, the Siderius Nuncius ultimately changed the grounds upon which natural philosophical argument and debate was carried out. In this new empirical arena, the Galilean science would eventually prevail. (shrink)

Stanford’s argument against scientific realism focuses on theories, just as many earlier arguments from inconceivability have. However, there are possible arguments against scientific realism involving unconceived (or inconceivable) entities of different types: observations, models, predictions, explanations, methods, instruments, experiments, and values. This paper charts such arguments. In combination, they present the strongest challenge yet to scientific realism.

An analogue of Arrow’s theorem has been thought to limit the possibilities for multi-criterial theory choice. Here, an example drawn from Toy Science, a model of theories and choice criteria, suggests that it does not. Arrow’s assumption that domains are unrestricted is inappropriate in connection with theory choice in Toy Science. There are, however, variants of Arrow’s theorem that do not require an unrestricted domain. They require instead that domains are, in a technical sense, ‘rich’. Since there are rich domains (...) in Toy Science, such theorems do constrain theory choice to some extent—certainly in the model and perhaps also in real science. (shrink)

How should we determine the distribution of psychological traits—such as Theory of Mind, episodic memory, and metacognition—throughout the Animal kingdom? Researchers have long worried about the distorting effects of anthropomorphic bias on this comparative project. A purported corrective against this bias was offered as a cornerstone of comparative psychology by C. Lloyd Morgan in his famous “Canon”. Also dangerous, however, is a distinct bias that loads the deck against animal mentality: our tendency to tie the competence criteria for cognitive capacities (...) to an exaggerated sense of typical human performance. I dub this error “anthropofabulation”, since it combines anthropocentrism with confabulation about our own prowess. Anthropofabulation has long distorted the debate about animal minds, but it is a bias that has been little discussed and against which the Canon provides no protection. Luckily, there is a venerable corrective against anthropofabulation: a principle offered long ago by David Hume, which I call “Hume’s Dictum”. In this paper, I argue that Hume’s Dictum deserves a privileged place next to Morgan’s Canon in the methodology of comparative psychology, illustrating my point through a discussion of the debate over Theory of Mind in nonhuman animals. (shrink)

This review is a critical discussion of three main claims in Debs and Redhead’s thought-provoking book Objectivity, Invariance, and Convention. These claims are: (i) Social acts impinge upon formal aspects of scientific representation; (ii) symmetries introduce the need for conventional choice; (iii) perspectival symmetry is a necessary and sufficient condition for objectivity, while symmetry simpliciter fails to be necessary.

Most scientists and philosophers of science recognize that, when it comes to accepting and rejecting theories in science, considerations that have to do with simplicity, unity, symmetry, elegance, beauty or explanatory power have an important role to play, in addition to empirical considerations. Until recently, however, no one has been able to give a satisfactory account of what simplicity (etc.) is, or how giving preference to simple theories is to be justified. But in the last few years, two different but (...) related accounts have appeared, both of which address the above issues. On the one hand, James McAllister has argued that aesthetic criteria in science reflect scientists' judgements about what kind of theory is most likely to be empirically successful, based on the relative empirical success and failure of different kinds of theories in the past. Scientists employ what McAllister dubs "the aesthetic induction". On the other hand, I have argued that we need to see science as making a hierarchy of metaphysical assumptions about the comprehensibility and knowability of the universe, these assumptions asserting less and less as one ascends the hierarchy. One of the more substantial of these assumptions is that the universe is physically comprehensible. The key non-empirical feature a body of fundamental theories in physics must possess to be acceptable is unity. The better such a body of theory exemplifies the metaphysical thesis that the universe is physically comprehensible, in the sense that it has a unified dynamic structure, so the more acceptable such a body of theory is, from this standpoint. This affects not just theoretical physics, but the whole of natural science. In this paper I compare and contrast, and try to assess impartially the relative merits of, these two views. (shrink)

Philosophers of science discuss whether theory selection depends on aesthetic judgments or criteria, and whether these putatively aesthetic features are genuinely extra-epistemic. As examples, judgments involving criteria such as simplicity and symmetry are often cited. However, other theory selection criteria, such as fecundity, coherence, internal consistency, and fertility, more closely match those criteria used in art contexts and by scholars working in aesthetics. Paying closer attention to the way these criteria are used in art contexts allows us to understand some (...) evaluative and developmental practices in scientific theory selection as genuinely aesthetic, enlarging the scope of the goals of science. (shrink)

Scientists often use aesthetic values in the evaluation and choice of theories. Aesthetic values are not only regarded as leading to practically more useful theories but are often taken to stand in a special epistemic relation to the truth of a theory such that the aesthetic merit of a theory is evidence of its truth. This paper explores what aesthetic considerations influence scientists' reasoning, how such aesthetic values relate to the utility of a scientific theory, and how one can justify (...) the epistemic role for such values. The paper examines ways in which the link between beauty and truth can be defended, the challenges facing such accounts, and explores alternative epistemic roles for aesthetic values in scientific practice. (shrink)

"Sir Hermann Bondi, NatureThe late S. Chandrasekhar was best known for his discovery of the upper limit to the mass of a white dwarf star, for which he received ...

Roger Scruton is dismissed by those who do not care to study him as a conservative philosopher. This review shows how Scruton is in fact more a theologian than a philosopher. This review is contrarian in tone to the reviews of Scruton to be found online and restores him as the rightful heir to theologians like Barth, Bultmann etc.

This article explores the implications of Michael Polanyi's concept of Tacit Knowledge for religious belief in general, and Christianity in particular, by investigating the relationship of tacit knowledge to commitment in scientific investigation, and extrapolating that relationship to commitments in the area of religious belief.

Conservatism about perceptual justification tells us that we cannot have perceptual justification to believe p unless we also have justification to believe that perceptual experiences are reliable. There are many ways to maintain this thesis, ways that have not been sufficiently appreciated. Most of these ways lead to at least one of two problems. The first is an over-intellectualization problem, whereas the second problem concerns the satisfaction of the epistemic basing requirement on justified belief. I argue that there is at (...) least one Conservative view that survives both difficulties, a view which has the further ability to undercut a crucial consideration that has supported Dogmatist views about perceptual justification. The final section explores a tension between Conservatism and the prospects of having a completely general account of propositional justification. Ironically, the problem is that Conservatives seem committed to making the acquisition of propositional justification too easy. My partial defense of Conservatism concludes by suggesting possible solutions to this problem. (shrink)

A scientific theory, according to Popper, can be legitimately saved from falsification by introducing an auxiliary hypothesis to generate new, falsifiable predictions. Also, if there are suspicions of bias or error, the researchers might introduce an auxiliary falsifiable hypothesis that would allow testing. But this technique can not solve the problem in general, because any auxiliary hypothesis can be challenged in the same way, ad infinitum. To solve this regression, Popper introduces the idea of ​​a basic statement, an empirical statement (...) that can be used both to determine whether a given theory is falsifiable and, if necessary, to corroborate falsification assumptions. DOI: 10.13140/RG.2.2.22162.09923. (shrink)

În această lucrare argumentez faptul că, în ciuda criticilor teoriei falsificabilității propuse de Karl Popper pentru demarcarea între știință și ne-știință, în principal pseudoștiință, acest criteriu este încă foarte util, și perfect valabil după perfecționarea lui de către Popper și adepții lui. Mai mult, chiar și în versiunea sa inițială, considerată de Lakatos ca ”dogmatică”, Popper nu a afirmat că această metodologie este un criteriu absolut de demarcare: un singur contra-exemplu nu este suficient pentru a falsifica o teorie; mai mult, (...) o teorie poate fi salvată în mod legitim de falsificare prin introducerea unei ipoteze auxiliare. În comparație cu teoria lui Kuhn a revoluțiilor, de care el însuși s-a dezis ulterior transformând-o într-o teorie a ”micro-revoluțiilor”, consider că metodologia de demarcare a lui Popper, împreună cu dezvoltarea ulterioară propusă de acesta, inclusiv coroborarea și verosimilitudinea, deși imperfectă, nu numai că este valabilă și azi, dar este încă cea mai bună metodologie de demarcare. Pentru argumentare, m-am folosit de principalele lucrări ale lui Popper care tratează această problemă, și a principalilor săi critici și susținători. După o scurtă prezentare a lui Karl Popper, și o introducere în problema demarcației și metodologia falsificabilității, trec în revistă principalele critici aduse și argumentele susținătorilor săi, accentuând pe ideea că Popper nu a pus niciodată semnul egalității între falsificare și respingere. În final prezint propriile concluzii în această problemă. (shrink)

The problem of rational prediction, launched by Wesley Salmon, is without doubt the Achilles heel of the critical method defended by Popper. In this paper, I assess the response given both by Popper and by the popperian Alan Musgrave to this problem. Both responses are inadequate and thus the conclusion of Salmon is reinforced: without appeal to induction, there is no way to make of the practical prediction a rational action. Furthermore, the critical method needs to be vindicated if one (...) pretends that its application be suitable for the preference of hypothesis. I argue that the nature of this vindication is such that it may be applied also to induction. Thus, to be a popperian is a good reason also to be an inductivist. (shrink)

Imre Lakatos' views on the philosophy of mathematics are important and they have often been underappreciated. The most obvious lacuna in this respect is the lack of detailed discussion and analysis of his 1976a paper and its implications for the methodology of mathematics, particularly its implications with respect to argumentation and the matter of how truths are established in mathematics. The most important themes that run through his work on the philosophy of mathematics and which culminate in the 1976a paper (...) are (1) the (quasi-)empirical character of mathematics and (2) the rejection of axiomatic deductivism as the basis of mathematical knowledge. In this paper Lakatos' later views on the quasi-empirical nature of mathematical theories and methodology are examined and specific attention is paid to what this view implies about the nature of mathematical argumentation and its relation to the empirical sciences. (shrink)

In their critique of Klein (2014a), Trafimow and Earp present two theses. First, they argue that, contra Klein, a well-specified theory is not a necessary condition for successful replication. Second, they contend that even when there is a well-specified theory, replication depends more on auxiliary assumptions than on theory proper. I take issue with both claims, arguing that (a) their first thesis confuses a material conditional (what I said) with a modal claim (T&E’s misreading of what I said), and (b) (...) their second thesis has the unfortunate consequence of refuting their first thesis. (shrink)

Hempel, Popper, and Kuhn argue that to be scientific is to be testable, to be falsifiable, and most nearly to do normal science, respectively. I argue that to be scientific is largely to be interactive, offering some examples from science to show that the ideas from different fields of science interact with one another. The results of the interactions are that hypotheses become more plausible, new phenomena are explained and predicted, we understand phenomena from a new perspective, and our worldview (...) becomes simpler. I also argue that given that the interactions are impressive features of science, astrology and religion would be regarded as science, provided that there are similar interactions in those enterprises. (shrink)

The paper demonstrates that falsifiability is fundamental to learning. We prove the following theorem for statistical learning and sequential prediction: If a theory is falsifiable then it is learnable -- i.e. admits a strategy that predicts optimally. An analogous result is shown for universal induction.

From the early-1950s on, F.A. Hayek was concerned with the development of a methodology of sciences that study systems of complex phenomena. Hayek argued that the knowledge that can be acquired about such systems is, in virtue of their complexity (and the comparatively narrow boundaries of human cognitive faculties), relatively limited. The paper aims to elucidate the implications of Hayek’s methodology with respect to the specific dimensions along which the scientist’s knowledge of some complex phenomena may be limited. Hayek’s fallibilism (...) was an essential (if not always explicit) aspect of his arguments against the defenders of both socialism ([1935] 1948, [1940] 1948) and countercyclical monetary policy ([1975] 1978); yet, despite the fact that his conceptions of both complex phenomena and the methodology appropriate to their investigation imply that ignorance might beset the scientist in multiple respects, he never explicated all of these consequences. The specificity of a scientific prediction depends on the extent of the scientist’s knowledge concerning the phenomena under investigation. The paper offers an account of the considerations that determine the extent to which a theory’s implications prohibit the occurrence of particular events in the relevant domain. This theory of “predictive degree” both expresses and – as the phenomena of scientific prediction are themselves complex in Hayek’s sense – exemplifies the intuition that the specificity of a scientific prediction depends on the relevant knowledge available. (shrink)

In paragraph 21 of his "Logic of Scientific Discovery", Karl Popper characterizes with the help of two seemingly synonymous definitions the falsifiability of a theory as a logical relation between the theory itself and its basic statements. It is shown that his definitions do not agree with each other, and this result is applied to the problem of the falsifiability of contradictions, to the difference between falsifiable and empirical statements and to the demarcation criterion.

We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity measures count the number of hypotheses about a dataset that a learning algorithm falsifies when it finds the classifier in its repertoire minimizing empirical risk. It then follows from that the future performance of predictors on unseen data is controlled in part by how many hypotheses the learner falsifies. As a corollary we show that empirical VC-entropy quantifies the message (...) length of the true hypothesis in the optimal code of a particular probability distribution, the so-called actual repertoire. (shrink)

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical learning (...) theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information. (shrink)

The paper aims to expound on the issue of science being different from non science or prescience in the form of the scientific methodology used. Popper’s method of falsifiability ensures the aim of science to be successful. The aim of science which also needs a critical attitude, can enable scientific progress by rejecting inductivism as its scientific methodology. Popper’s view on what the aim of science is and why and how inductivism fails in the case of science, along with examples (...) from history of science besides its impact on philosophical foundations of science, has been stressed in the paper. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Karl Popper rightly contests the possibility of a verification of basic statements. At the same time he strictly believes in the possibility of growth of empirical knowledge. Knowledge growth, however, is only possible if empirical theories can be falsified. This raises the question, how theories can be falsified, if a verification of those statements that falsify theories – i.e. basic statements – is not possible. This problem is often referred to as the “basic problem” or “problem of the empirical basis”. (...) In this paper I show that – from a logical point of view – a falsification of theories is possible without a verification of basic state-ments. Furthermore I show that knowledge growth in the empirical sciences will be possible if two assumptions are valid. These assumptions can neither be proven nor falsified. However, they have to be postulated by everybody in eve-ryday life. (shrink)

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the Universe or its initial state this becomes a particularly pressing issue. How to assess the probability of the Universe as a whole is empirically ambiguous, since we can examine only part of a single realisation of the system under investigation: at some point, data will (...) run out. We review the basics of applying Bayesian statistical explanation to the Universe as a whole. We argue that a conventional Bayesian approach to model inference generally fails in such circumstances, and cannot resolve, e.g., the so-called 'measure problem' in inflationary cosmology. Implicit and non-empirical valuations inevitably enter model assessment in these cases. This undermines the possibility to perform Bayesian model comparison. One must therefore either stay silent, or pursue a more general form of systematic and rational model assessment. We outline a generalised axiological Bayesian model inference framework, based on mathematical lattices. This extends inference based on empirical data (evidence) to additionally consider the properties of model structure (elegance) and model possibility space (beneficence). We propose this as a natural and theoretically well-motivated framework for introducing an explicit, rational approach to theoretical model prejudice and inference beyond data. (shrink)

A ‘duality’ is a formal mapping between the spaces of solutions of two empirically equivalent theories. In recent times, dualities have been found to be pervasive in string theory and quantum field theory. Naïvely interpreted, duality-related theories appear to make very different ontological claims about the world—differing in e.g. space-time structure, fundamental ontology, and mereological structure. In light of this, duality-related theories raise questions familiar from discussions of underdetermination in the philosophy of science: in the presence of dual theories, what (...) is one to say about the ontology of the world? In this paper, we undertake a comprehensive and non-technical survey of the landscape of possible ontological interpretations of duality-related theories. We provide a significantly enriched and clarified taxonomy of options—several of which are novel to the literature. (shrink)

Should philosophers prefer simpler theories? Huemer (Philos Q 59:216–236, 2009) argues that the reasons to prefer simpler theories in science do not apply in philosophy. I will argue that Huemer is mistaken—the arguments he marshals for preferring simpler theories in science can also be applied in philosophy. Like Huemer, I will focus on the philosophy of mind and the nominalism/Platonism debate. But I want to engage with the broader issue of whether simplicity is relevant to philosophy.

In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

Scientists often use aesthetic values in the evaluation and choice of theories. Aesthetic values are not only regarded as leading to practically more useful theories but are often taken to stand in a special epistemic relation to the truth of a theory such that the aesthetic merit of a theory is evidence of its truth. This paper explores what aesthetic considerations influence scientists' reasoning, how such aesthetic values relate to the utility of a scientific theory, and how one can justify (...) the epistemic role for such values. The paper examines ways in which the link between beauty and truth can be defended, the challenges facing such accounts, and explores alternative epistemic roles for aesthetic values in scientific practice. (shrink)

Metaphysicians frequently appeal to the idea that theoretical simplicity is truth conducive in metaphysics, in the sense that, all other things being equal, simpler metaphysical theories are more likely to be true. In this paper I defend the notion that theoretical simplicity is truth conducive in metaphysics, against several recent objections. I do not give any direct arguments for the thesis that simplicity is truth conducive in metaphysics, since I am aware of no such arguments. I do argue, however, that (...) there is no special problem with the notion that simplicity is truth conducive in metaphysics. More specifically, I argue that if you accept the idea that simplicity is truth conducive in science, then it would be objectionably arbitrary to reject the idea that simplicity is truth conducive in metaphysics. (shrink)

The laws of classical logic are taken to be logical truths, which in turn are taken to hold objectively. However, we might question our faith in these truths: why are they true? One general approach, proposed by Putnam [8] and more recently Dickson [3] or Maddy [5], is to adopt empiricism about logic. On this view, logical truths are true because they are true of the world alone – this gives logical truths an air of objectivity. Putnam and Dickson both (...) take logical truths to be true in virtue of the world’s structure, given by our best empirical theory, quantum mechanics. This assumes a determinate logical structure of the world given by quantum mechanics. Here, I argue that this assumption is false, and that the world’s logical structure, and hence the related ‘true’ logic, are underdetermined. This leads to what I call empirical conventionalism. (shrink)

The twin goals of this essay are: to investigate a family of cases in which the goal of guaranteed convergence to the truth is beyond our reach; and to argue that each of three strands prominent in contemporary epistemological thought has undesirable consequences when confronted with the existence of such problems. Approaches that follow Reichenbach in taking guaranteed convergence to the truth to be the characteristic virtue of good methods face a vicious closure problem. Approaches on which there is a (...) unique rational doxastic response to any given body of evidence can avoid incoherence only by rendering epistemology a curiously limited enterprise. Bayesian approaches rule out humility about one’s prospects of success in certain situations in which failure is typical. (shrink)

Scientific realism (Putnam 1975; Psillos 1999) and relative realism (Mizrahi 2013) claim that successful scientific theories are approximately true and comparatively true, respectively. A theory is approximately true if and only if it is close to the truth. A theory is comparatively true if and only if it is closer to the truth than its competitors are. I argue that relative realism is more skeptical about the claims of science than it initially appears to be and that it can explain (...) neither the success nor the failure of science. Hence, it is not a promising competitor to scientific realism. (shrink)

A platitude that took hold with Kuhn is that there can be several equally good ways of balancing theoretical virtues for theory choice. Okasha recently modelled theory choice using technical apparatus from the domain of social choice: famously, Arrow showed that no method of social choice can jointly satisfy four desiderata, and each of the desiderata in social choice has an analogue in theory choice. Okasha suggested that one can avoid the Arrow analogue for theory choice by employing a strategy (...) used by Sen in social choice, namely, to enhance the information made available to the choice algorithms. I argue here that, despite Okasha’s claims to the contrary, the information-enhancing strategy is not compelling in the domain of theory choice. (shrink)

The controversy over the old ideal of “value-free science” has cooled significantly over the past decade. Many philosophers of science now agree that even ethical and political values may play a substantial role in all aspects of scientific inquiry. Consequently, in the last few years, work in science and values has become more specific: Which values may influence science, and in which ways? Or, how do we distinguish illegitimate from illegitimate kinds of influence? In this paper, I argue that this (...) problem requires philosophers of science to take a new direction. I present two case studies in the influence of values on scientific inquiry: feminist values in archaeology and commercial values in pharmaceutical research. I offer a preliminary assessment of these cases, that the influence of values was legitimate in the feminist case, but not in the pharmaceutical case. I then turn to three major approaches to distinguish legitimate from illegitimate influences of values, including the distinction between epistemic and non-epistemic values and Heather Douglas’ distinction between direct and indirect roles for values. I argue that none of these three approaches gives an adequate analysis of the two cases. In the concluding section, I briefly sketch my own approach, which draws more heavily on ethics than the others, and is more promising as a solution to the current problem. This is the new direction in which I think science and values should move. (shrink)

The aim of this paper is to show that science, understood as pure research, ought not to be affected by non-epistemic values and thus to defend the traditional ideal of value-free science. First, we will trace the distinction between science and technology, arguing that science should be identified with pure research and that any non-epistemic concern should be di­rected toward technology and technological research. Second, we will examine different kinds of values and the roles they can play in scientific research (...) to argue that science understood as pure research is mostly and in any case ought to be value-free. Third, we will consider and dismiss some widespread arguments that aim to defend, especially at a normative level, the inevitable value-ladenness of science. Finally, we will briefly return to the connections among science, technology, and values. (shrink)

For four decades it has been argued that we need to adopt a new conception of science called aim-oriented empiricism. This has far-reaching implications and repercussions for science, the philosophy of science, academic inquiry in general, conception of rationality, and how we go about attempting to make progress towards as good a world as possible. Despite these far-reaching repercussions, aim-oriented empiricism has so far received scant attention from philosophers of science. Here, sixteen objections to the validity of the argument for (...) aim-oriented empiricism are subjected to critical scrutiny. (shrink)

When scientists choose one theory over another, they reject out of hand all those that are not simple, unified or explanatory. Yet the orthodox view of science is that evidence alone should determine what can be accepted. Nicholas Maxwell thinks he has a way out of the dilemma.

A scientific theory, in order to be accepted as a part of theoretical scientific knowledge, must satisfy both empirical and non-empirical requirements, the latter having to do with simplicity, unity, explanatory character, symmetry, beauty. No satisfactory, generally accepted account of such non-empirical requirements has so far been given. Here, a proposal is put forward which, it is claimed, makes a contribution towards solving the problem. This proposal concerns unity of physical theory. In order to satisfy the non-empirical requirement of unity, (...) a physical theory must be such that the same laws govern all possible phenomena to which the theory applies. Eight increasingly demanding versions of this requirement are distinguished. Some implications for other non-empirical requirements, and for our understanding of science are indicated. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

There is a widely shared belief that the higher level sciences can provide better explanations than lower level sciences. But there is little agreement about exactly why this is so. It is often suggested that higher level explanations are better because they omit details. I will argue instead that the preference for higher level explanations is just a special case of our general preference for informative, logically strong, beliefs. I argue that our preference for informative beliefs entirely accounts for why (...) higher level explanations are sometimes better – and sometimes worse – than lower level explanations. The result is a step in the direction of the unity of science hypothesis. (shrink)

The issue of common method variance and bias in Indonesia still has not gained much attention; even the terminology is less popular, except among psychometric enthusiasts and experts. In fact, the potential for common method variance and bias infiltrating in research results is very high, especially in studies that use a single method, a single source, and concurrent design, which are highly favored by psychological lecturers and researchers in Indonesia. This paper is a critical review, exposing the debate and serious (...) impact regarding common method variance and bias, as well as procedures for detecting, addressing and correcting its effects. The author hoped this paper contributes in filling the gap in the literature, especially in Psychology Research Methodology text books in the Indonesian language, so that psychological researches in Indonesia continue to increase their quality and to have their better place in international publications. (shrink)

Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence —when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a (...) sufficient independence condition for warranting robustness arguments. We show that OI evidence can collectively confirm a hypothesis to a lower degree than individual lines of evidence, contrary to the standard assumption undergirding usual robustness arguments. We employ Bayesian networks to represent the ideal empirical scenario for a robustness argument and a variety of ways in which empirical scenarios can fall short of this ideal. (shrink)

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates (...) moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference. (shrink)