Several philosophers of science claim that scientific toy models afford knowledge of possibility, but answers to the question of why toy models can be expected to competently play this role are scarce. The main line of reply is that toy models support possibility claims insofar as they are credible. I raise a challenge for this credibility-thesis, drawing on a familiar problem for imagination-based modal epistemologies, and argue that it remains unanswered in the current literature. The credibility-thesis has a long (...) way to go if it is to account for the epistemic merits of toy models. (shrink)

Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the social (...) sciences. The most important difference between the social sciences and the natural sciences with respect to modeling is that in the social sciences powerful and well confirmed background theories (like Newtonian mechanics, quantum mechanics or the theory of relativity in physics) do not exist in the social sciences. Therefore, an epistemology of models that is formed on the role model of physics may not be appropriate for the social sciences. I discuss the challenges that modeling faces in the social sciences and point out their epistemological consequences. The most important consequences are that greater emphasis must be placed on empirical validation than on theoretical validation and that the relevance of purely theoretical simulations is strongly limited. (shrink)

Mathematics clearly plays an important role in scientific explanation. Debate continues, however, over the kind of role that mathematics plays. I argue that if pure mathematical explananda and physical explananda are unified under a common explanation within science, then we have good reason to believe that mathematics is explanatory in its own right. The argument motivates the search for a new kind of scientific case study, a case in which pure mathematical facts and physical facts are explanatorily unified. I (...) argue that it is possible for there to be such cases, and provide some toy examples to demonstrate this. I then identify a potential source of scientific case studies as a guide for future work. (shrink)

Chemical visualizations and models are special kinds of situated, inductive arguments. In this paper, I examine several historical case studies—an archive of images from museums, special collections, and popular magazines—as examples of emergent practices of physical modeling as theoretical play which became the basis for molecular biology and structural chemistry. Specifically, I trace a legacy of visualization tools that starts with Archibald Scott Cooper and Friedrich Kekulé in the late 1800s, crystallizes as material manipulatives in Kekulé’s student Jacobus Henricus Van’t (...) Hoff and his folded paper “toys,” is legitimized in the California lab of Linus Pauling, and is glorified in the popular imaginary with James Watson and Francis Crick’s model of DNA. My tracing then follows several threads into contemporary modeling practices. I ultimately argue that modeling play, originally outside of the boundary of deductive, positivist science, is now an accepted mode of inductive reasoning in these related chemical fields. (shrink)

The article introduces a thematic issue of the journal Theory of Science that attempts to revive the category of "philosophi- cal toys" - objects and instruments designed for experimental scientific research that simultaneously played crucial role in the creation of the modern visual culture. It claims that to fully understand their nature and the kind of experience philosophical toys induce, it is necessary to situate their origins in eighteenth-century experimental science and aesthetics and proposes to approach (...) them as perceptual and cognitive extensions. (shrink)

The Marburg neo-Kantians argue that Hermann von Helmholtz's empiricist account of the a priori does not account for certain knowledge, since it is based on a psychological phenomenon, trust in the regularities of nature. They argue that Helmholtz's account raises the 'problem of validity' (Gueltigkeitsproblem): how to establish a warranted claim that observed regularities are based on actual relations. I reconstruct Heinrich Hertz's and Ludwig Wittgenstein's Bild theoretic answer to the problem of validity: that scientists and philosophers can depict the (...) necessary a priori constraints on states of affairs in a given system, and can establish whether these relations are actual relations in nature. The analysis of necessity within a system is a lasting contribution of the Bild theory. However, Hertz and Wittgenstein argue that the logical and mathematical sentences of a Bild are rules, tools for constructing relations, and the rules themselves are meaningless outside the theory. Carnap revises the argument for validity by attempting to give semantic rules for translation between frameworks. Russell and Quine object that pragmatics better accounts for the role of a priori reasoning in translating between frameworks. The conclusion of the tale, then, is a partial vindication of Helmholtz's original account. (shrink)

The central topic of this essay consists into establishing a relation between two dimensions of formation: the conceptual process of creating philo- sophical toys - that is of reelaborating existing philosophical concepts, mainly deriving from the thought of Gilles Deleuze and Félix Guattari, in terms of their potential as ‘operative constructs' - and their parallel redeployment towards the specific problem of analyz- ing a recent transdisciplinary artwork. By means of this strategical shift, theory looses its character of explanation and (...) illustration. Philosophy as toy becomes rather the matter of evaluating the com- plexity of a specific artistic composition in terms of its aesthetic potential. It contributes towards developing meta- stable conditions of mutual resonance between heterogeneous modalities of creation. (shrink)

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his pocket (...) shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (shrink)

Nineteenth-century optical toys that showcase illusions of motion such as the phenakistoscope, zoetrope, and praxinoscope, have enjoyed active “afterlives” in the twentieth and twenty-first centuries. Contemporary incarnations of the zoetrope are frequently found in the realms of fine art and advertising, and they are often much larger than their nineteenth-century counterparts. This article argues that modern-day optical toys are able to conjure feelings of wonder and spectacle equivalent to their nineteenth-century antecedents because of their adjustment in scale. Exploring (...) a range of contemporary philosophical toys found in arts, entertainment, and advertising contexts, the article discusses various technical adjustments made to successfully “scale up” optical toys, including the replacement of hand-spun mechanisms with larger sources of motion and the use of various means such as architectural features and stroboscopic lights to replace traditional shutter mechanisms such as the zoetrope’s dark slots. Critical consideration of scale as a central feature of these installations reconfigures the relationship between audience and device. Large-scale adaptations of optical toys revise the traditional conception of the user, who is able to tactilely manipulate and interact with the apparatus, instead positing a viewer who has less control over the illusion’s operation and is instead a captive audience surrounded by the animation. It is primarily through their adaptation of scale that contemporary zoetropes successfully elicit wonder as scientific spectacles from their audiences today. (shrink)

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these questions. This report (...) sets out some possible approaches, and describes some of the ways government is already engaging with these issues. (shrink)

Moral, social, political, and other “nonepistemic” values can lead to bias in science, from prioritizing certain topics over others to the rationalization of questionable research practices. Such values might seem particularly common or powerful in the social sciences, given their subject matter. However, I argue first that the well-documented phenomenon of motivated reasoning provides a useful framework for understanding when values guide scientific inquiry (in pernicious or productive ways). Second, this analysis reveals a parity thesis: values influence the social (...) and natural sciences about equally, particularly because both are so prominently affected by desires for social credit and status, including recognition and career advancement. Ultimately, bias in natural and social science is both natural and social— that is, a part of human nature and considerably motivated by a concern for social status (and its maintenance). Whether the pervasive influence of values is inimical to the sciences is a separate question. (shrink)

I first quickly outline what I think grasping is, and suggest that it is both among our basic aims of inquiry and not essentially tied to belief, justification, or knowledge. Then, I briefly look at some places in the metaphysics of science in which it looks like our aim of grasping and our aim in knowing—or perhaps more specifically in knowing the explanations for things—might seem to conflict. I will use this conflict to support a broader view: sometimes, we (...) might develop philosophical views or theories—and even endorse them—in order to better grasp them, regardless of whether we genuinely believe them, or are justified in so doing. At other times, we may be aiming at propositional knowledge. These aims can come apart, and perhaps even systematically come apart. A pluralism about the value of those aims doesn’t entail an “anything goes” attitude with respect to how we think about what philosophical views to put forward, defend, or endorse, however—far from it. Instead, it suggests that what counts as a virtue of a philosophical theory depends on our aims in espousing it. If philosophers have distinct aims at the meta-level, it will be hard for them to engage in joint theory evaluation at the first-order level. At least all three of theoretical virtues, evaluative judgments of philosophical views, and what attitudes we ought to have towards the views we ourselves espouse will vary according to our guiding metaphilosophical aims. (shrink)

Some of the most significant policy responses to cases of fraudulent and questionable conduct by scientists have been to strengthen professionalism among scientists, whether by codes of conduct, integrity boards, or mandatory research integrity training programs. Yet there has been little systematic discussion about what professionalism in scientific research should mean. In this paper I draw on the sociology of the professions and on data comparing codes of conduct in science to those in the professions, in order to examine (...) what precisely the model of professionalism implies for scientific research. I argue that professionalism, more than any other single organizational logic, is appropriate for scientific research, and that codes of conduct for scientists should strengthen statements concerning scientific autonomy and competence, as well as the scientific service ideal. (shrink)

Consensus and disagreement play important roles in the practice, development, and dissemination of science. This raises a host of important philosophical questions. Some of these issues are conceptual: When, exactly, does a scientific agreement count as a consensus? And in what sense, if any, is disagreement the opposite of consensus? Other questions concern the role of consensus and disagreement in the development of science: For example, is consensus on central methodological issues and assumptions necessary for scientific work to (...) proceed normally? Yet other questions are epistemological: From a layperson’s perspective, does the presence of a scientific consensus ever indicate that the relevant theory is probably correct? If so, what are the conditions under which it does so? Relatedly, should scientists themselves also defer to the consensus position among their peers whenever such a consensus exists? Or should they instead evaluate consensus theories for themselves, or even actively aim to dissent against such theories? (shrink)

Social and medical scientists frequently produce empirical generalizations that involve concepts partly defined by value judgments. These generalizations, which have been called ‘mixed claims’, raise interesting questions. Does the presence of them in science imply that science is value-laden? Is the value-ladenness of mixed claims special compared to other kinds of value-ladenness of science? Do we lose epistemically if we reformulate these claims as conditional statements? And if we want to allow mixed claims in science, do (...) we need a new account of how to reconcile values with objectivity? Alexandrova (2017, 2018) offers affirmative answers to these questions. In responding to Alexandrova’s arguments, this discussion note motivates negative ones and in doing so casts new light on mixed claims. (shrink)

This highly multidisciplinary collection discusses an increasingly important topic among scholars in science and technology studies: objectivity in science. It features eleven essays on scientific objectivity from a variety of perspectives, including philosophy of science, history of science, and feminist philosophy. Topics addressed in the book include the nature and value of scientific objectivity, the history of objectivity, and objectivity in scientific journals and communities. Taken individually, the essays supply new methodological tools for theorizing what is (...) valuable in the pursuit of objective knowledge and for investigating its history. The essays offer many starting points, while suggesting new avenues of research. Taken collectively, the essays exemplify the very virtues of objectivity that they theorize—in reading them together, the reader can sense various anxieties about the dangerously subjective in our age and locate commonalities of concern as well as differences of approach. As a result, the volume offers an expansive vision of a research community seeking a communal understanding of its own methods and its own epistemic anxieties, struggling to enunciate the key problems of knowledge of our time and offer insight into how to overcome them. -/- (Contributors: Alex Csiszar, Scott Edgar, Peter Galison, Ian Hacking, Sandra Harding, Moira Howes, Paolo Savoia, Judy Segal, Joan Steigerwald, and Alison Wylie). (shrink)

Introduction to the Synthese Special Issue on Disagreement in Science.

As a result of the world-wide COVID-19 epidemic, an internal tension in the goals of medicine has come to the forefront of public debate. Medical professionals are continuously faced with a tug of...

I develop a theory of counterfactuals about relative computability, i.e. counterfactuals such as 'If the validity problem were algorithmically decidable, then the halting problem would also be algorithmically decidable,' which is true, and 'If the validity problem were algorithmically decidable, then arithmetical truth would also be algorithmically decidable,' which is false. These counterfactuals are counterpossibles, i.e. they have metaphysically impossible antecedents. They thus pose a challenge to the orthodoxy about counterfactuals, which would treat them as uniformly true. What’s more, I (...) argue that these counterpossibles don’t just appear in the periphery of relative computability theory but instead they play an ineliminable role in the development of the theory. Finally, I present and discuss a model theory for these counterfactuals that is a straightforward extension of the familiar comparative similarity models. (shrink)

I argue that philosophical studies of the virtues of creativity should attend to the ways that our conceptions of human creativity may be grounded in conceptions of human nature or the nature of reality. I consider and reject claims in this direction made by David Bohm and Paul Feyerabend. The more compelling candidate is the account of science, creativity, and human nature developed by the early Marx. Its guiding claim is that the forms of creativity enabled by the sciences (...) are ultimately valuable insofar as they advance our emancipation from a state of existential alienation. I end by encouraging future investigations of such vertical explanations of the significance of certain virtues in the context of scientific enquiry. (shrink)

Philosophers of science now broadly agree that doing good science involves making non-epistemic value judgments. I call attention to two very different normative standards which can be used to evaluate such judgments: standards grounded in ethics and standards grounded in political philosophy. Though this distinction has not previously been highlighted, I show that the values in science literature contain arguments of each type. I conclude by explaining why this distinction is important. Seeking to determine whether some value-laden (...) determination meets substantive ethical standards is a very different endeavor from seeking to determine if it is politically legitimate. (shrink)

One way in which to address the intriguing relations between science and reality is to work via the models (mathematical structures) of formal scientific theories which are interpretations under which these theories turn out to be true. The so-called 'statement approach' to scientific theories -- characteristic for instance of Nagel, Carnap, and Hempel --depicts theories in terms of 'symbolic languages' and some set of 'correspondence rules' or 'definition principles'. The defenders of the oppositionist non-statement approach advocate an analysis where (...) the language in which the theory is formulated plays a much smaller role. They hold that foundational problems in the various sciences can in general be better addressed by focusing on the models these sciences employ than by reformulating the products of these sciences in some appropriate language. My model-theoretic realist account of science lies decidedly within the non-statement context, although I retain the notion of a theory as a deductively closed set of sentences (expressed in some appropriate language), in this paper I shall focus -- against the background of a model-theoretic account of science -- on the approach to the reality-science dichotomy offered by Nancy Cartwright and briefly comment on a few aspects of Roy Bhaskar's transcendental realism. I shall, in conclusion, show how a model-theoretic approach such as mine can combine the best of these two approaches. (shrink)

In the first half of the 20 th century, philosophers of science used to sustain that the correct theory acceptance in science derived from their conforming to certain rules. However, from the historicist and practical turn in the philosophy of science, the theory acceptance started to be analyzed based on values rather than on a priori established rules. In this article, I will present four paradigmatic positions on the role of values in science. The first position, (...) articulated by Hugh Lacey, defends a regulative ideal of 'impartiality' in the acceptance of scientific theories as established. The other positions convey arguments that seem to conflict with this ideal. I characterize them as 'blind spot argument', 'inductive risk argument' and 'trust-based acceptance argument'. Based on this analysis, I will defend two main theses. My first thesis is that the ideal of impartiality is compatible with the arguments just mentioned. My second thesis is that the defense of impartiality has the advantage of providing a support for the epistemic authority of properly established scientific knowledge. Following Lacey, I will argue that theories can only be accepted as established under specified domains of phenomena. However, theories are accepted for other purposes, for example, when they are adopted to develop research or when they are endorsed to inform the legitimacy of an action. In such cases of theory acceptance, impartiality is neither possible nor desirable, which requires the support of other ideals. (shrink)

The task of Philosophy in Science (PinS) is to use philosophical tools to help solve scientific problems. This article describes how I stumbled into this line of work and then addressed several topics in philosophy of biology—units of selection, cladistic parsimony, robustness and trade-offs in model building, adaptationism, and evidence for common ancestry—often in collaboration with scientists. I conclude by offering advice for would-be PinS practitioners.

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination in problem-solving. (...) But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (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)

Metaphysical considerations aside, today’s inheritors of the tradition of natural philosophy are primarily scientists. However, they are oblivious to the human factor involved in science and in seeing how political, religious, and other ideologies contaminate our visions of nature. In general, philosophers observe human (historical, sociological, and psychological) processes within the construction of theories, as well as in the development of scientific activity itself. -/- In our time, feminism—along with accompanying ideas of identity politics under the slogan “diversity, inclusion, (...) equity”—has emerged in science policies. The vast majority of scientists (including myself) are convinced that discrimination is reprehensible. We also believe that all individuals of any sex, race, ethnic group, or ideology should be valued in academia solely based on his or her merits and potential through equality programs. However, as I will show in this article, political indoctrination has inadmissibly undertaken the struggle for equality in academic institutions in Western countries. I argue here that universities and research institutes should be politically free (neutral) to encourage academic freedom. -/- One negative aspect of equality programs is that worldwide, scientists are harassed for expressing opinions related to the “gender” issue. This situation severely restricts scientists’ freedom of expression, even within the limits of the law. Codes of conduct extending beyond legal boundaries are examples of this issue. Scientists who express their views about “gender” are often harassed, bullied, and socially or academically excluded. Thus, we are witnessing a wave of proselytizing in research institutes and science-associated media. Today, there is widespread biased propaganda of “victimhood”. This propaganda proposes positive discrimination and increasing women’s participation in unnatural ways. It also bends the history of science by overvaluing the creations of forgotten women, offering lectures on indoctrination, organizing congresses on gender and science, and persecuting anyone who sees the subject differently. All of this covered by a multitude of associations that financially benefit from these discourses through succulent subsidies of public money. Apparently, feminism is no longer about fighting against discrimination. Instead, it is about imposing an ideology and giving more power to one group of people. Thus, we must ask whether the end justifies the means. (shrink)

Development in all of its stages, from organizing the vision and strategy to implementing plans, requires policy-making. We show that the division of labor and specialization of sciences and some philosophical doctrines cause the emergence of technocracy in policies. Technocracy makes development not happen in the direction of public welfare. For this reason, for sustainable development, we need institutions, strategies, and philosophical contexts that provide a democratic ground for the possibility of criticizing and reforming policies.

The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view (...) of theories; the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science. (shrink)

In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track (...) can be captured by three features - namely, quasi-axiomaticity (QA), generative potential (GP), and empirical shielding (ES) - which are exhibited to a maximal degree by the examples Friedman deploys, particularly in his analysis of Newtonian mechanics. I argue that not all varieties of 'constitutivity' can be captured by the kind of gradualism implicit in Friedman's view, although developing the gradualism itself might provide useful insights. To show this, I analyse the function of the Hardy-Weinberg principle (HWP) in population genetics in terms of its QA, GP, and ES. Whereas the HWP does not count as constitutive in classical philosophical interpretations (Sober 1984), nor does it within Friedman's framework, it does nonetheless perform a minimally constitutive function. By means of historical details and considerations on the prospects of replacing the HWP, I show that the HWP is minimally constitutive by being a counterfactual instantiation of a paradigmatically constitutive stability principle, where the latter might itself be regarded as an enabling condition for a variety of modelling practices across the sciences. (shrink)

This chapter examines the status of inference to the best explanation in naturalistic metaphysics. The methodology of inference to the best explanation in metaphysics is studied from the perspective of contemporary views on scientific explanation and explanatory inferences in the history and philosophy of science. This reveals serious shortcomings in prevalent attempts to vindicate metaphysical "explanationism" by reference to similarities between science and naturalistic metaphysics. This critique is brought out by considering a common gambit of methodological unity: (1) (...) Both metaphysics and science employ inference to the best explanation. (2) One has no reason to think that if explanationism is truth-conducive in science, it is not so in metaphysics. (3) One has a positive reason to think that if explanationism is truth-conducive in science, it is also so in metaphysics. (shrink)

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

This article develops an account of distributive epistemic justice in the production of scientific knowledge. We identify four requirements: (a) science should produce the knowledge citizens need in order to reason about the common good, their individual good and pursuit thereof; (b) science should produce the knowledge those serving the public need to pursue justice effectively; (c) science should be organized in such a way that it does not aid the wilful manufacturing of ignorance; and (d) when (...) making decisions about epistemic risks, scientists should make sure that there aren’t social groups or weighty interests that are neglected. After discussing these requirements, we examine the relationship between discriminatory and distributive epistemic injustice in science and argue that they often compound each other. (shrink)

The English language now dominates scientific communications. Yet, many scientists have English as their second language. Their English proficiency may therefore often be more limited than that of a ‘native speaker’, and their scientific contributions (e.g. manuscripts) in English may frequently contain linguistic features that disrupt the fluency of a reader’s, or listener’s information processing even when the contributions are understandable. Scientific gatekeepers (e.g. journal reviewers) sometimes cite these features to justify negative decisions on manuscripts. Such justifications may rest on (...) the prima facie plausible assumption that linguistic characteristics that hinder fast and easy understandability of scientific contributions are epistemically undesirable in science. I shall raise some doubts about this assumption by drawing on empirical research on processing fluency and its biasing effects. I also argue that directing scientists with English as a foreign language toward approaching ‘native-level’ English can have the negative consequence of reducing their potential to make scientific belief formation more reliable. These points suggest that one seemingly compelling justification for linguistically discriminating against scientific contributions in ‘non-native’ English is questionable and that the common insistence by scientific gatekeepers on ‘native-like’ English may be epistemically harmful to science. (shrink)

In “Milvian Bridges in Science, Religion, and Theology: Debunking Arguments and Cultural Evolution,” Lari Launonen and Aku Visala engage with an EDA against religious belief that appeals to cultural rather than biological evolution. According to this EDA, religious beliefs are unjustified, not because they are generated by biologically shaped cognitive processes that are unreliable as far as those beliefs are concerned but because they are generated by cultural processes that select for those beliefs for their ability to produce prosocial (...) behavior rather than for their truth sensitivity. Scientific beliefs, by contrast, are truth-sensitive because their cultural fitness depends on their power to produce accurate predictions. Their truth sensitivity explains the great amount of convergence on them that exists across cultures. In response to the EDA in question, Launonen and Visala argue that the difference between science and religion is actually more a matter of degree than a matter of kind, that there is considerable cross-cultural convergence on theistic and Christian beliefs, and that folk Christian beliefs, just as folk scientific ones, are truth-sensitive to the extent that they are constrained by expert beliefs. (shrink)

Scientific realists believe both what a scientific theory says about observables and unobservables. In contrast, scientific antirealists believe what a scientific theory says about observables, but not about unobservables. I argue that scientific realism is a more useful doctrine than scientific antirealism in science classrooms. If science teachers are antirealists, they are caught in Moore’s paradox when they help their students grasp the content of a scientific theory, and when they explain a phenomenon in terms of a scientific (...) theory. Teachers ask questions to their students to check whether they have grasped the content of a scientific theory. If the students are antirealists, they are also caught in Moore’s paradox when they respond positively to their teachers’ questions, and when they explain a phenomenon in terms of a scientific theory. Finally, neither teachers nor students can understand phenomena in terms of scientific theories, if they are antirealists. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing (...) on two recent proposals which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

Philosophers of science often make reference — whether tacitly or explicitly — to the notion of a scientific community. Sometimes, such references are useful to make our object of analysis tractable in the philosophy of science. For others, tracking or understanding particular features of the development of science proves to be tied to notions of a scientific community either as a target of theoretical or social intervention. We argue that the structure of contemporary scientific research poses two (...) unappreciated, or at least underappreciated, challenges to this concept of the “scientific community” in the philosophy of science. In particular, we will present two case studies from robotics research, broadly construed, which show that (1) the boundedness of the scientific community is threatened when private citizens can develop scientific and technological advances at minimal expense (democratization), and (2) the discreteness of scientific research programs is threatened by the complexly interrelated environment of contemporary scientific work (interconnectivity). Taken together, the extent of democratization and interconnectivity present a significant challenge for any practically oriented philosophy of science, one which we hope will be taken on directly by philosophers in the future. (shrink)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, overgeneralized (...) conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science. (shrink)

Recent epistemology of modality has seen a growing trend towards metaphysics-first approaches. Contrastingly, this paper offers a more philosophically modest account of justifying modal claims, focusing on the practices of scientific modal inferences. Two ways of making such inferences are identified and analyzed: actualist-manipulationist modality and relative modality. In AM, what is observed to be or not to be the case in actuality or under manipulations, allows us to make modal inferences. AM-based inferences are fallible, but the same holds for (...) practically all empirical inquiry. In RM, modal inferences are evaluated relative to what is kept fixed in a system, like a theory or a model. RM-based inferences are more certain but framework-dependent. While elements from both AM and RM can be found in some existing accounts of modality, it is worth highlighting them in their own right and isolating their features for closer scrutiny. This helps to establish their relevant epistemologies that are free from some strong philosophical assumptions often attached to them in the literature. We close by showing how combining these two routes amounts to a view that accounts for a rich variety of modal inferences in science. (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

Understanding science requires appreciating the values it presupposes and its social context. Both the values that scientists hold and their social context can affect scientific communication. Philosophers of science have recently begun studying scientific communication, especially as it relates to public policy. Some have proposed “guiding principles for communicating scientific findings” to promote trust and objectivity. This paper contributes to this line of research in a novel way using behavioural experimentation. We report results from three experiments testing judgments (...) about the trustworthiness, competence and objectivity of scientists. More specifically, we tested whether such judgments are affected by three factors: consulting or not consulting nonscientists, conducting research under a restrictive or non-restrictive governmental communication policy, and the source of a lab’s funding (i.e., government funding, private funding, or a combination of the two). We found that each of these factors affects ordinary judgments of trustworthiness, competence and objectivity. These findings support several recommendations that could help improve scientific communication and communication policies. (shrink)

Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one (...) is to produce an analy-sis of the role that models and inferences play in science. The second one is to produce an analysis of the way models and inferences are constructed, especial-ly in the light of what science tells us about our cognitive abilities. The papers collected in this volume go both ways. (shrink)

In our interactions with science, we are often vulnerable; we do not have complete control of the situation and there is a risk that we, or those we love, might be harmed. This is not an emotionall...

What attitude should we take toward a scientific theory when it competes with other scientific theories? This question elicited different answers from instrumentalists, logical positivists, constructive empiricists, scientific realists, holists, theory-ladenists, antidivisionists, falsificationists, and anarchists in the philosophy of science literature. I will summarize the diverse philosophical responses to the problem of underdetermination, and argue that there are different kinds of underdetermination, and that they should be kept apart from each other because they call for different responses.

Scientists often communicate using generic generalizations, which are unquantified generalizations such as ‘Americans overestimate social class mobility’ or ‘sound waves carry gravitational mass’. In this paper, I explain the role of such generic generalizations in science, based on a novel theory about their characteristic meaning. According to this theory, a scientific generalization of the form ‘Ks are F’ says that F is one property based on which category K qualifies as a scientific kind. Because what it takes to qualify (...) as a scientific kind varies depending on the discipline, what a generic sentence entails also varies. Based on this semantic theory, I discuss the benefits and drawbacks of using generic language in science. (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)

A conspicuous feature of contemporary modelling practices is the use of the same mathematical forms and modelling methods across different scientific domains. This model transfer raises many philosophical questions concerning, for example, the exact object of transfer, the relationship between the model and the target domain, the specific challenges such transfer confronts, and the ways in which model transfer relates to scientific progress. While the interest in studying model transfer has increased among philosophers of science in recent years, the (...) phenomenon has not yet received its due attention. The literature is scattered and much of it has addressed questions around the factors that might explain model transfer, such as whether the different target phenomena to which a model is applied eventually prove to be structurally and dynamically similar, or whether they have to share more fundamental ontological features that explain the interdisciplinary success of distinct models. This chapter surveys the existing literature on model transfer with the main goal of highlighting the main findings of existing discussions and pointing out open issues whose discussion would improve our understanding of this highly relevant phenomenon in science. (shrink)

Dubljević and company’s proposed approach for incorporating a socio-political perspective into neuroethics has clear potential to help mitigate the effects of research ‘hype’ relating to neuroethics. Their approach serves as a social regulation meant to improve the realizability of neuroethics research. Drawing on Dubljević et al. s suggestion, we consider how incorporating a socio-political perspective in other scientific disciplines could help the scientific community as a whole move beyond the infamous ‘reproducibility crisis’ in science. The reproducibility crisis is a (...) concern in science stemming from the revelation that most scientific results are difficult, or impossible, to replicate (Frias-Navarro et al., 2020). By applying the four principles proposed by Dubljević et al., the scientific community can avoid many of the pitfalls that have led to the reproducibility crisis, such as the file drawer effect, a publication bias preventing negative results from being published, or the publish-or-perish culture - the pressure for scientists to publish highly influential papers in high impact journals in order to keep their funding (Rosenthal, 1979; Begley & Ioannidis, 2015). As such, we argue that, in its final form, this socio-political framework begs for true open science, wherein systematically sharing data would enable enlightened policymaking by showing a picture closer to the ground-level realities of scientific research. (shrink)