According to a widely shared generic conception of inferential justification—‘the standard conception’—an agent is inferentially justified in believing that p only if she has antecedently justified beliefs in all the non-redundant premises of a good argument for p. This conception tends to serve as the starting-point in contemporary debates about the nature and scope of inferential justification: as neutral common ground between various competing, more specific, conceptions. But it’s a deeply problematic starting-point. This paper explores three questions that haven’t been (...) given the attention they deserve, that complicate the application of the standard conception to cases, and that reveal it to be underspecified at the core—in ways that aren’t resolved but inherited by more specific (extant) versions of it. The goal isn’t to answer the questions, but to articulate them, explain what turns on them, and invite a critical re-examination of the standard conception. (shrink)

There are two senses of ‘what scientists know’: An individual sense (the separate opinions of individual scientists) and a collective sense (the state of the discipline). The latter is what matters for policy and planning, but it is not something that can be directly observed or reported. A function can be defined to map individual judgments onto an aggregate judgment. I argue that such a function cannot effectively capture community opinion, especially in cases that matter to us.

Some philosophers think that there is a gap between is and ought which necessarily makes normative enquiry a different kind of thing than empirical science. This position gains support from our ability to explicate our inferential practices in a way that makes it impermissible to move from descriptive premises to a normative conclusion. But we can also explicate them in a way that allows such moves. So there is no categorical answer as to whether there is or is not a (...) gap. The question of an is-ought gap is a practical and strategic matter rather than a logical one, and it may properly be answered in different ways for different questions or at different times. (shrink)

This paper offers a general characterization of underdetermination and gives a prima facie case for the underdetermination of the topology of the universe. A survey of several philosophical approaches to the problem fails to resolve the issue: the case involves the possibility of massive reduplication, but Strawson on massive reduplication provides no help here; it is not obvious that any of the rival theories are to be preferred on grounds of simplicity; and the usual talk of empirically equivalent theories misses (...) the point entirely. (If the choice is underdetermined, then the theories are not empirically equivalent!) Yet the thought experiment is analogous to a live scientific possibility, and actual astronomy faces underdetermination of this kind. This paper concludes by suggesting how the matter can be resolved, either by localizing the underdetermination or by defeating it entirely. Introduction A brief preliminary Around the universe in 80 days Some attempts at resolving the problem 4.1 Indexicality 4.2 Simplicity 4.3 Empirical equivalence 4.4 Is this just a philosophers' fantasy? Move along... ...nothing to see here 6.1 Rules of repetition 6.2 Some possible replies Conclusion. (shrink)

It has been common wisdom for centuries that scientific inference cannot be deductive; if it is inference at all, it must be a distinctive kind of inductive inference. According to demonstrative theories of induction, however, important scientific inferences are not inductive in the sense of requiring ampliative inference rules at all. Rather, they are deductive inferences with sufficiently strong premises. General considerations about inferences suffice to show that there is no difference in justification between an inference construed demonstratively or ampliatively. (...) The inductive risk may be shouldered by premises or rules, but it cannot be shirked. Demonstrative theories of induction might, nevertheless, better describe scientific practice. And there may be good methodological reasons for constructing our inferences one way rather than the other. By exploring the limits of these possible advantages, I argue that scientific inference is neither of essence deductive nor of essence inductive. (shrink)

Background theories in science are used both to prove and to disprove that theory choice is underdetermined by data. The alleged proof appeals to the fact that experiments to decide between theories typically require auxiliary assumptions from other theories. If this generates a kind of underdetermination, it shows that standards of scientific inference are fallible and must be appropriately contextualized. The alleged disproof appeals to the possibility of suitable background theories to show that no theory choice can be timelessly or (...) noncontextually underdetermined: Foreground theories might be distinguished against different backgrounds. Philosophers have often replied to such a disproof by focussing their attention not on theories but on Total Sciences. If empirically equivalent Total Sciences were at stake, then there would be no background against which they could be differentiated. I offer several reasons to think that Total Science is a philosophers' fiction. No respectable underdetermination can be based on it. (shrink)

Using the context of controversies surrounding evolutionary developmental biology (EvoDevo) and the possibility of an Extended Evolutionary Synthesis, I provide an account of theory structure as idealized theory presentations that are always incomplete (partial) and shaped by their conceptual content (material rather than formal organization). These two characteristics are salient because the goals that organize and regulate scientific practice, including the activity of using a theory, are heterogeneous. This means that the same theory can be structured differently, in part because (...) theory presentations (as idealizations) intentionally depart from different features known to be present in a theory. Since there are diverse and potentially incompatible theory structures derived from heterogeneous goals found in scientific practices, a question arises about the absence of a unifying theory structure in the background. The notion of a “theory façade” offers a fruitful perspective on this potentially unsettling result. (shrink)

Scientific explanation is a perennial topic in philosophy of science, but the literature has fragmented into specialized discussions in different scientific disciplines. An increasing attention to scientific practice by philosophers is (in part) responsible for this fragmentation and has put pressure on criteria of adequacy for philosophical accounts of explanation, usually demanding some form of pluralism. This commentary examines the arguments offered by Fagan and Woody with respect to explanation and understanding in scientific practice. I begin by scrutinizing Fagan's concept (...) of collaborative explanation, highlighting its distinctive advantages and expressing concern about several of its assumptions. Then I analyze Woody's attempt to reorient discussions of scientific explanation around functional considerations, elaborating on the wider implications of this methodological recommendation. I conclude with reflections on synergies and tensions that emerge when the two papers are juxtaposed and how these draw attention to critical issues that confront ongoing philosophical analyses of scientific explanation. (shrink)

We propose a new account of calibration according to which calibrating a technique shows that the technique does what it is supposed to do. To motivate our account, we examine an early twentieth-century debate about chlorophyll chemistry and Mikhail Tswett’s use of chromatographic adsorption analysis to study it. We argue that Tswett’s experiments established that his technique was reliable in the special case of chlorophyll without relying on either a theory or a standard calibration experiment. We suggest that Tswett broke (...) the experimenters’ regress by appealing to material facts in the common ground for chemists at the time. (shrink)

As scientists start to adopt machine learning (ML) as one research tool, the security of ML and the knowledge generated become a concern. In this paper, I explain how supervised ML can be improved with better data ontology, or the way we make categories and turn information into data. More specifically, we should design data ontology in such a way that is consistent with the knowledge that we have about the target phenomenon so that such ontology can help us make (...) the inductive leap. I do so by thinking through a thought experiment, Goodman’s New Riddle of Induction (Fact, fiction, and forecast, Harvard University Press, 1955). Goodman’s riddle helps flesh out three problems of induction: (1) the problem of equal goodies, that there are often too many equally good inductive results given the same data; (2) the problem of diverging performance, that these equally good results can give opposite predictions in the future; and (3) the problem of mediocrity, that when averaged across all equally possible datasets and tasks, no inductive algorithm outperforms any other. I show that all these three problems are manifested as real obstacles in ML practice, namely, the Rashomon effect (Breiman in Stat Sci 16(3):199–231, 2001), the problem of underspecification (D’Amour et al. in J Mach Learn Res, 2020, https://doi.org/10.48550/arXiv.2011.03395 ), and the No Free Lunch theorem (Wolpert in Neural Comput 8(7):1341–90, 1996, https://doi.org/10.1162/neco.1996.8.7.1341 ). Lastly, I argue that proper data ontology can help mitigate these problems and I demonstrate how using concrete examples from climate science. This research highlights the links between philosophers’ discussions of induction and implications in ML practice. (shrink)

In this paper I offer a coherentist justification of induction along the lines of a Sellarsian coherence theory. On this coherence theory, a proposition is justified if we can answer all objections raised against it in our social practice of demanding justification and responding to such demands. On the basis of this theory of justification, I argue that we are justified in accepting the uniformity of nature partly because we have no alternative but to accept it for rationally pursuing our (...) epistemic goal. In addition, my coherentist view explains which inductive inferences it is rational to accept. Furthermore, my coherentist view also explains why we can hardly determine a particular numerical value x such that we can draw the conclusion ‘it is rational to accept that p’ from the premise ‘the numerical probability of p is greater than or equal to x’. (shrink)

With respect to inductive reasoning, there are at least two broad projects that have been of interest to philosophers. The first project is that of accurately describing paradigmatic instances of inductive reasoning in the sciences and in everyday life. Thus, we might ask, of some particular historical episode, how exactly Newton, or Darwin, or Einstein arrived at some conclusion on the basis of the evidence that was before him. The second project is one of justification. The task here is that (...) of showing why paradigmatic inductive reasoning is good reasoning, or why skeptical challenges which purport to undermine the legitimacy of such reasoning fail to do so. As I understand it, this second, justificatory project prominently includes, but is not limited to, the task of either solving or dissolving Hume’s skeptical critique of induction.[1] Neither of these projects is trivial. Indeed, many think that we are currently far from successfully completing either one. But in any case, it would seem that the descriptive project has a certain priority to the justification project. After all, how could one justify our inductive practices, or defend them against skeptical challenge, in the absence of some reasonably detailed and accurate description of those practices? Given this apparent priority, it is a striking fact that the justification project has often been pursued in the absence of any significant attention to the project of accurate description. In particular, a great deal of the traditional discussion of Hume’s problem of induction has proceeded against the background of hopelessly crude models of our actual inductive practice—a fact sometimes acknowledged by participants in such discussions themselves. Plausibly, the thought which underlies this procedure is the following: whatever force Hume’s critique ultimately possesses, that force is not tied to the specific content of the general rules or principles that we follow in reasoning inductively. Rather, the force of Hume’s critique depends on our following any general rules or principles at all.. (shrink)

This paper analyzes what it means for philosophy of science to be normative. It argues that normativity is a multifaceted phenomenon rather than a general feature that a philosophical theory either has or lacks. It analyzes the normativity of philosophy of science by articulating three ways in which a philosophical theory can be normative. Methodological normativity arises from normative assumptions that philosophers make when they select, interpret, evaluate, and mutually adjust relevant empirical information, on which they base their philosophical theories. (...) Object normativity emerges from the fact that the object of philosophical theorizing can itself be normative, such as when philosophers discuss epistemic norms in science. Metanormativity arises from the kind of claims that a philosophical theory contains, such as normative claims about science as it should be. Distinguishing these three kinds of normativity gives rise to a nuanced and illuminating view of how philosophy of science can be normative. (shrink)

This paper explains what’s wrong with a Hume-inspired argument for skepticism about induction. Hume’s argument takes as a premise that inductive reasoning presupposes that the future will resemble the past. I explain why that claim is not plausible. The most plausible premise in the vicinity is that inductive reasoning from E to H presupposes that if E then H. I formulate and then refute a skeptical argument based on that premise. Central to my response is a psychological explanation for how (...) people judge that if E then H without realizing that they thereby settled the matter rationally. (shrink)

One of the most lively debates on scientific understanding is standardly presented as a controversy between the so-called factivists, who argue that understanding implies truth, and the non-factivists whose position is that truth is neither necessary nor sufficient for understanding. A closer look at the debate, however, reveals that the borderline between factivism and non-factivism is not as clear-cut as it looks at first glance. Some of those who claim to be quasi-factivists come suspiciously close to the position of their (...) opponents, the non-factivist, from whom they pretend to differ. The non-factivist, in turn, acknowledges that some sort of ‘answering to the facts’ is indispensable for understanding. This paper discusses an example of convergence of the initially rival positions in the debate on understanding and truth: the use of the same substitute for truth by the quasi-factivist Kareem Khalifa and the non-factivists Henk de Regt and Victor Gijsbers. It is argued that the use of ‘effectiveness’ as a substitute for truth by both parties is not an occasional coincidence of terms, it rather speaks about a deeper similarity which have important implications for understanding the essential features of scientific understanding. (shrink)

Framing systematics as a field consistent with scientific inquiry entails that inferences of phylogenetic hypotheses have the goal of producing accounts of past causal events that explain differentially shared characters among organisms. Linking observations of characters to inferences occurs by way of why-questions implied by data matrices. Because of their form, why-questions require the use of common-cause theories. Such theories in phylogenetic inferences include natural selection and genetic drift. Selection or drift can explain ‘morphological’ characters but selection cannot be causally (...) applied to sequences since fitness differences cannot be directly associated with individual nucleotides or amino acids. The relation of selection to sequence data is by way of downward or top-down causation from those phenotypes upon which selection occurs. The application of phylogenetic inference to explain sequence data is thus restricted to instances where drift is the relevant theory; those nucleotides or amino acids that can be explained via downward causation are precluded from inclusion in the data matrix. The restrictions on the inclusion of sequence data in phylogenetic inferences equally apply to species hypotheses, precluding the more restrictive approach known as DNA barcoding. Not being able to discern drift and selection as relevant causal mechanisms can severely constrain the inclusion and explanations of sequence data. Implications of such exclusion are discussed in relation to the requirement of total evidence. (shrink)

Three competing ‘methods’ have been endorsed for inferring phylogenetic hypotheses: parsimony, likelihood, and Bayesianism. The latter two have been claimed superior because they take into account rates of sequence substitution. Can rates of substitution be justified on its own accord in inferences of explanatory hypotheses? Answering this question requires addressing four issues: (1) the aim of scientific inquiry, (2) the nature of why-questions, (3) explanatory hypotheses as answers to why-questions, and (4) acknowledging that neither parsimony, likelihood, nor Bayesianism are inferential (...) actions leading to explanatory hypotheses. The aim of scientific inquiry is to acquire causal understanding of effects. Observation statements of organismal characters lead to implicit or explicit why-questions. Those questions, conveyed in data matrices, assume the truth of observation statements, which is contrary to subsequently invoking substitution rates within inferences to phylogenetic hypotheses. Inferences of explanatory hypotheses are abductive in form, such that some version of an evolutionary theory(ies) is/are included or implied. If rates of sequence evolution are to be considered, it must be done prior to, rather than within abduction, which requires renaming those putatively-shared nucleotides subject to substitution rates. There are, however, no epistemic grounds for renaming characters to accommodate rates, calling into question the legitimacy of causally accounting for sequence data. (shrink)

This paper discusses the role that appeals to theoretical simplicity have played in the debate between nativists and empiricists in cognitive science. Both sides have been keen to make use of such appeals in defence of their respective positions about the structure and ontogeny of the human mind. Focusing on the standard simplicity argument employed by empiricist-minded philosophers and cognitive scientists—what I call “the argument for minimal innateness”—I identify various problems with such arguments—in particular, the apparent arbitrariness of the relevant (...) notions of simplicity at work. I then argue that simplicity ought not be seen as a theoretical desideratum in its own right, but rather as a stand-in for other desirable features of theories. In this deflationary vein, I argue that the best way of interpreting the argument for minimal innateness is to view it as an indirect appeal to various potential biological constraints on the amount of innate structure that can wired into the human mind. I then consider how nativists may respond to this biologized version of the argument, and discuss the role that similar biological concerns have played in recent nativist theorizing in the Minimalist Programme in generative linguistics. (shrink)

This paper revisits the debate between Harry Collins and Allan Franklin, concerning the experimenters’ regress. Focusing my attention on a case study from recent psychology (regarding experimental evidence for the existence of a Mozart Effect), I argue that Franklin is right to highlight the role of epistemological strategies in scientific practice, but that his account does not sufficiently appreciate Collins’s point about the importance of tacit knowledge in experimental practice. In turn, Collins rightly highlights the epistemic uncertainty (and skepticism) surrounding (...) much experimental research. However, I will argue that his analysis of tacit knowledge fails to elucidate the reasons why scientists often are (and should be) skeptical of other researchers’ experimental results. I will present an analysis of tacit knowledge in experimental research that not only answers to this desideratum, but also shows how such skepticism can in fact be a vital enabling factor for the dynamic processes of experimental knowledge generation. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

Some philosophers of physics recently expressed their skepticism about causation (Norton 2003b, 2007). However, this is not new. The view that causation does not refer to any ontological category perhaps can be attributed to Hume, Kant and Russell. On the other hand, some philosophers (Wesley Salmon and Phil Dowe) view causation as a physical process and some others (Cartwright) view causation as making claims about capacities possessed by objects. The issue about the ontological status of causal claims involves issues concerning (...) the ontological status of capacity, modality and dispositional claims. In this paper, my goal is to show that without engaging metaphysical debates about the ontological status of causal claims, it can be shown that we can objectively assign truth values to these statements. I argue that for causal claims to be objective we don't need to postulate the existence of special facts (specific to causal claims) in addition to ordinary physical facts described by physical theories. This, I think, is enough to justify the usefulness of this concept in certain branches (may be all) of science. Once this is achieved, there is no need to engage in unnecessary metaphysical debates. So, even if advanced physical theories don't mention this notion, causal reasoning can still be important in understanding the world not in the sense that science discovers special ontological category called causation but in the sense that we come to know certain facts about the world. (shrink)

The notion of empirical adequacy has received recent philosophical attention, especially within the framework of the semantic approach. Empirical adequacy, as explicated in the semantic approach, concerns the relationship between empirical substructures and some phenomena. The aim here is to differentiate this notion of empirical adequacy from one concerning the relationship between data and phenomena. Distinguishing each notion of empirical adequacy emphasizes different aspects of scientific practice—one concerning theory-development from the basis of an established theory, the other concerning theory-development from (...) the basis of data-fitting, where established theory may not foster further development. To illustrate this contrast, an example from financial economics is considered. (shrink)

In this essay, I take the role as friendly commentator and call attention to three potential worries for John D. Norton’s material theory of induction. I attempt to show that his “principle argument” is based on a false dichotomy, that the idea that facts ultimately derive their license from matters of fact is debatable, and that one of the core implications of his theory is untenable for historical and fundamental reasons.

Charles Lyell’s Principles of Geology is widely regarded as one of the great works of 19th century science, and one of the most influential works in the entire history of the earth sciences. Yet the standard critical interpretation of the Principles makes such high regard and influence look puzzling at best. We are told, for instance, that Lyell’s argument rests on a contentious a priori methodological distinction between scientific and non-scientific explanations, the former featuring observed causes at their present intensities, (...) the latter featuring anything else. 2 We are also told that Lyell simply assumes a priori that. (shrink)

Recent literature in the scientific realism debate has been concerned with a particular species of statistical fallacy concerning base-rates, and the worry that no matter how predictively successful our contemporary scientific theories may be, this will tell us absolutely nothing about the likelihood of their truth if our overall sample space contains enough empirically adequate theories that are nevertheless false. In response, both realists and anti-realists have switched their focus from general arguments concerning the reliability and historical track-records of our (...) scientific methodology, to a series of specific arguments and case-studies concerning our reasons to believe individual scientific theories to be true. Such a development however sits in tension with the usual understanding of the scientific realism debate as offering a second-order assessment of our first-order scientific practices, and threatens to undermine the possibility of a distinctive philosophical debate over the approximate truth of our scientific theories. I illustrate this concern with three recent attempts to offer a more localised understanding of the scientific realism debate—due to Stathis Psillos, Juha Saatsi, and Kyle Stanford—and argue that none of these alternatives offer a satisfactory response to the problem. (shrink)

William Whewell’s account of induction differs dramatically from the one familiar from twentieth-century debates. I argue that Whewell’s induction can be usefully understood by comparing the difference between his views and more standard accounts to contemporary debates between semantic and syntactic views of theories: rather than understanding inductive inference as capturing a relationship between sentences or propositions, Whewell understands it as a method for constructing a model of the world. The difference between this view and the more familiar picture of (...) induction is reflected in other aspects of Whewell’s philosophy of science, particularly his treatment of consilience and the order of discovery. (shrink)

Pierre Duhem’s influential argument for holism relies on a view of the role that background theory plays in testing: according to this still common account of “auxiliary hypotheses,” elements of background theory serve as truth-apt premises in arguments for or against a hypothesis. I argue that this view is mistaken. Rather than serving as truth-apt premises in arguments, auxiliary hypotheses are employed as “epistemic tools”: instruments that perform specific tasks in connecting our theoretical questions with the world but that are (...) not premises in arguments. On the resulting picture, the acceptability of an auxiliary hypothesis depends not on its truth but on contextual factors such as the task or purpose it is put to and the other tools employed alongside it. (shrink)

Convincing disputes about explanatory reductionism in the philosophy of biology require a clear and precise understanding of what a reductive explanation in biology is. The central aim of this book is to provide such an account by revealing the features that determine the reductive character of a biological explanation. Chapters I-IV provide the ground, on which I can then, in Chapter V, develop my own account of explanatory reduction in biology: Chapter I reveals the meta-philosophical assumptions that underlie my analysis (...) of reduction, Chapter II introduces the previous debate about reduction in the philosophy of biology by pointing out the most crucial lessons one should learn from this debate, Chapter III critically discusses the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far, and Chapter IV clarifies in what ways the issue of reduction is entangled with the issue of explanation. In Chapter V I present my own account of explanatory reduction. My main claim is that reductive explanations in the biological sciences possess three main characteristics: they explain the behavior of a biological system S, first, exclusively in terms of factors that are located on a lower level of organization than S, second, by focusing on factors that are internal to S , and third, by describing the genuine parts of S only as “parts in isolation”. This account is ontic because it traces the reductivity of an explanation back to certain relations that exist in the world. (shrink)

Das Dissertationsprojekt soll eine Verbindung zwischen zwei augenscheinlich separaten Debattensträngen in der kontemporären Wissenschaftstheorie erforschen. Das ist zum einen die Debatte um die humesche Doktrin, der zufolge es keine de-re notwendigen Verbindungen respektive modale Fakten in der natürlichen Welt gibt. Diese Debatte betrifft die Grundlagen der Naturwissenschaften sowie der Natur selbst. Und das ist zum anderen die Debatte um die materiale Theorie der Induktion, welche auf John D. Norton zurückgeht und die Grundlagen der Rationalität und Logik betrifft. Nach dieser Theorie (...) werden induktive Schlüsse qua relevanter, lokaler Hintergrundfakten zuverlässig. Norton bringt viele - in meinen Augen überzeugende - Beispiele für diese Theorie, lässt uns aber im Unklaren darüber, wie diese Hintergrundfakten induktive Schlüsse lizensieren können. Ich werde argumentieren, dass es sich bei diesen relevanten Fakten zumindest in einigen paradigmatischen Fällen um irreduzibel-modale oder modal grundierte Fakten handeln muss, ansonsten können diese die ihnen zugedachte Funktion nicht erfüllen. Infolgedessen steht der Humeanismus vor einer materialen Form des Induktionsproblems. -/- Meine Forschungshypothese lautet, dass es sich bei dem materialen Induktionsproblem um das eigentliche und zentrale Problem des Humeanismus handelt. Zum einen werden viele altbekannte Probleme des Humeanismus durch das materiale Induktionsproblem motiviert und bestärkt. Zum anderen begründet das materiale Induktionsproblem ein neues und tiefgreifendes Problem des Humeanismus. Es stellt sich darin, dass der Humeanismus den empirischen Erfolg unserer verfügbaren wissenschaftlichen und alltäglichen Gesetzesannahmen nicht zirkelfrei erklären kann. Darauf aufbauend formuliere ich ein Super-Wunderargument, das im Kern in einer Inferenz von den bisherigen empirischen Erfolgen unserer verfügbaren Gesetzesannahmen auf die Wahrheit des Anti-Humeanismus besteht. Dieses Argument steht im Zentrum meiner Arbeit. Alles Weitere wird im Kontext dieses Argumentes diskutiert und illustriert. Zu diesen Untersuchungen gehören die schrittweise Motivation des Argumentes durch das materiale Induktionsproblem, die Unterscheidung und Diskussion verschiedener logischer Formen des Argumentes, das Herausarbeiten der Vorteile sowie die Antizipation von möglichen Einwänden gegen das Argument. (shrink)

I offer a meta-level analysis of realist arguments for the reliability of ampliative reasoning about the unobservable. We can distinguish form-driven and content-driven arguments for realism: form-driven arguments appeal to the form of inductive inferences, whilst content-driven arguments appeal to their specific content. After regimenting the realism debate in these terms, I will argue that the content-driven arguments are preferable. Along the way I will discuss how my analysis relates to John Norton’s recent, more general thesis that the grounds for (...) licit induction are always material. (shrink)

This paper surveys and critically assesses existing theories of evidence with respect to four desiderata. A good theory of evidence should be both a theory of evidential support (i.e., be informative about what kinds of facts speak in favour of a hypothesis), and of warrant (i.e., be informative about how strongly a given set of facts speaks in favour of the hypothesis), it should apply to the non-ideal cases in which scientists typically find themselves, and it should be ‘descriptively adequate’, (...) i.e., able to adequately represent typical episodes of evidentiary reasoning. The theories surveyed here—Bayesianism, hypotheticodeductivism,satisfaction theories, error statistics as well as Achinstein’s and Cartwright’s theories—are all found wanting in important respects. I finally argue that a deficiency all these theories have in common is a neglect or underplaying of the epistemic context in which the episode of evidentiary reasoning takes place.Este artículo describe y valora críticamente diversas teorías de la evidencia en relación a cuatro desiderata. Una buena teoría de la evidencia debería ser tanto una teoría sobre el apoyo evidencial [evidential support] (ser informativa sobre qué tipos de hechos hablan a favor de la hipótesis) como sobre la justificación [warrant]; debería aplicarse en las situaciones no ideales en las que normalmente se encuentran los científicos; y debería ser ‘descriptivamente adecuada’, esto es, capaz de representar correctamente episodios típicos de razonamiento evidencial. Las teorías aquí revisadas—bayesianismo, hipotético-deductivismo, teorías de la satisfacibilidad, la estadística del error, así como las propuestas de Achinstein y Cartwright—se consideran deficientes en aspectos básicos. Argumentaré que un defecto común en todas ellas es que olvidan, o minusvaloran, el contexto epistémico en el que el episodio de razonamiento evidencial tiene lugar. (shrink)

Results on the observational indistinguishability of spacetimes demonstrate the impossibility of determining by deductive inference which is our spacetime, no matter how extensive a portion of the spacetime is observed. These results do not illustrate an underdetermination of theory by evidence, since they make no decision between competing theories and they make little contact with the inductive considerations that must ground such a decision. Rather, these results express a variety of indeterminism in which a specification of the observable past always (...) fails to fix the remainder of a spacetime. This form of indeterminism is more troubling than the familiar indeterminism of quantum theory. The inductive inferences that can discriminate among the different spacetime extensions of the observed past are here called “opaque,” which means that we cannot readily see the warrant that lies behind them. (shrink)

Inductive generalization asserts that what obtains in known instances can be generalized to all. Its original form is enumerative induction, the earliest form of inductive inference, and it has been elaborated in various ways, largely with the goal of extending its reach. Its principal problem is that it supplies no intrinsic notion of strength of support so that one cannot tell if the generalization has weak or strong support.

My dissertation explores the ways in which Rudolf Carnap sought to make philosophy scientific by further developing recent interpretive efforts to explain Carnap’s mature philosophical work as a form of engineering. It does this by looking in detail at his philosophical practice in his most sustained mature project, his work on pure and applied inductive logic. I, first, specify the sort of engineering Carnap is engaged in as involving an engineering design problem and then draw out the complications of design (...) problems from current work in history of engineering and technology studies. I then model Carnap’s practice based on those lessons and uncover ways in which Carnap’s technical work in inductive logic takes some of these lessons on board. This shows ways in which Carnap’s philosophical project subtly changes right through his late work on induction, providing an important corrective to interpretations that ignore the work on inductive logic. Specifically, I show that paying attention to the historical details of Carnap’s attempt to apply his work in inductive logic to decision theory and theoretical statistics in the 1950s and 1960s helps us understand how Carnap develops and rearticulates the philosophical point of the practical/theoretical distinction in his late work, offering thus a new interpretation of Carnap’s technical work within the broader context of philosophy of science and analytical philosophy in general. (shrink)

Non-trivial calculi of inductive inference are incomplete. This result is demonstrated formally elsewhere. Here the significance and background to the result is described. This note explains what is meant by incompleteness, why it is desirable, if only it could be secured, and it gives some indication of the arguments needed to establish its failure. The discussion will be informal, using illustrative examples rather than general results. Technical details and general proofs are presented in Norton.

Proponents of Bayesian confirmation theory believe that they have the solution to a significant, recalcitrant problem in philosophy of science. It is the identification of the logic that governs evidence and its inductive bearing in science. That is the logic that lets us say that our catalog of planetary observations strongly confirms Copernicus’ heliocentric hypothesis; or that the fossil record is good evidence for the theory of evolution; or that the 3oK cosmic background radiation supports big bang cosmology. The definitive (...) solution to this problem would be a significant achievement. The problem is of central importance to philosophy of science, for, in the end, what distinguishes science from myth making is that we have good evidence for the content of science, or at least of mature sciences, whereas myths are evidentially ungrounded fictions. The core ideas shared by all versions of Bayesian confirmation theory are, at a good first approximation, that a scientist’s beliefs are or should conform to a probability measure; and that the incorporation of new evidence is through conditionalization using Bayes’ theorem. While the burden of this chapter will be to inventory why critics believe this theory may not be the solution after all, it is worthwhile first to summarize here the most appealing virtues of this simple account. There are three. First, the theory reduces the often nebulous notion of a logic of.. (shrink)

State of the art paper on the problem of induction: how to justify the conclusion that ‘all Fs are Gs’ from the premise that ‘all observed Fs are Gs’. The most prominent theories of contemporary philosophical literature are discussed and analysed, such as: inductivism, reliabilism, perspective of laws of nature, rationalism, falsificationism, the material theory of induction and probabilistic approaches, according to Carnap, Reichenbach and Bayesianism. In the end, we discuss the new problem of induction of Goodman, raised by the (...) grue predicate. (shrink)

In a formal theory of induction, inductive inferences are licensed by universal schemas. In a material theory of induction, inductive inferences are licensed by facts. With this change in the conception of the nature of induction, I argue that Hume’s celebrated “problem of induction” can no longer be set up and is thereby dissolved.

This document collects discussion and commentary on issues raised in the workshop by its participants. Contributors are: Greg Frost-Arnold, David Harker, P. D. Magnus, John Manchak, John D. Norton, J. Brian Pitts, Kyle Stanford, Dana Tulodziecki.

I begin by making some distinctions between kinds of response to a skeptical claim, the purpose of which is to explain what I mean by a "dissolution" of the problem of induction, and to focus on one of the ways it can be implemented. I then argue that previous attempts to dissolve the problem in this way fail, present mine, and defend it. Finally, I show that the dissolution of the problem doesn't improve our normative situation and may even worsen (...) it. (shrink)

It is important to have an adequate model of uncertainty, since decisions must be made before the uncertainty can be resolved. For instance, flood defenses must be designed before we know the future distribution of flood events. It is standardly assumed that probability theory offers the best model of uncertain information. I think there are reasons to be sceptical of this claim. I criticise some arguments for the claim that probability theory is the only adequate model of uncertainty. In particular (...) I critique Dutch book arguments, representation theorems, and accuracy based arguments. Then I put forward my preferred model: imprecise probabilities. These are sets of probability measures. I offer several motivations for this model of uncertain belief, and suggest a number of interpretations of the framework. I also defend the model against some criticisms, including the so-called problem of dilation. I apply this framework to decision problems in the abstract. I discuss some decision rules from the literature including Levi’s E-admissibility and the more permissive rule favoured by Walley, among others. I then point towards some applications to climate decisions. My conclusions are largely negative: decision making under such severe uncertainty is inevitably difficult. I finish with a case study of scientific uncertainty. Climate modellers attempt to offer probabilistic forecasts of future climate change. There is reason to be sceptical that the model probabilities offered really do reflect the chances of future climate change, at least at regional scales and long lead times. Indeed, scientific uncertainty is multi-dimensional, and difficult to quantify. I argue that probability theory is not an adequate representation of the kinds of severe uncertainty that arise in some areas in science. I claim that this requires that we look for a better framework for modelling uncertainty. (shrink)

When radiocarbon dating techniques were applied to archaeological material in the 1950s they were hailed as a revolution. At last archaeologists could construct absolute chronologies anchored in temporal data backed by immutable laws of physics. This would make it possible to mobilize archaeological data across regions and time-periods on a global scale, rendering obsolete the local and relative chronologies on which archaeologists had long relied. As profound as the impact of 14C dating has been, it has had a long and (...) tortuous history now described as proceeding through three revolutions, each of which addresses distinct challenges of capturing, processing and packaging radiogenic data for use in resolving chronological puzzles with which archaeologists has long wrestled. In practice, mobilizing radiogenic data for archaeological use is a hard-won achievement; it involves multiple transformations that, at each step of the way, depend upon a diverse array of technical expertise and background knowledge. I focus on strategies of triangulation and traceability that establish the integrity of these data and their relevance as anchors for evidential reasoning in archaeology. (shrink)

Eliminative reasoning is a method that has been employed in many significant episodes in the history of science. It has also been advocated by some philosophers as an important means for justifying well-established scientific theories. Arguments for how eliminative reasoning is able to do so, however, have generally relied on a too narrow conception of evidence, and have therefore tended to lapse into merely heuristic or pragmatic justifications for their conclusions. This paper shows how a broader conception of evidence not (...) only can supply the needed justification but also illuminates the methodological significance of eliminative reasoning in a variety of contexts. (shrink)

The theory of concepts advanced in the dissertation aims at accounting for a) how a concept makes successful practice possible, and b) how a scientific concept can be subject to rational change in the course of history. Traditional accounts in the philosophy of science have usually studied concepts in terms only of their reference; their concern is to establish a stability of reference in order to address the incommensurability problem. My discussion, in contrast, suggests that each scientific concept consists of (...) three components of content: 1) reference, 2) inferential role, and 3) the epistemic goal pursued with the concept's use. I argue that in the course of history a concept can change in any of these three components, and that change in one component—including change of reference—can be accounted for as being rational relative to other components, in particular a concept's epistemic goal.This semantic framework is applied to two cases from the history of biology: the homology concept as used in 19th and 20th century biology, and the gene concept as used in different parts of the 20th century. The homology case study argues that the advent of Darwinian evolutionary theory, despite introducing a new definition of homology, did not bring about a new homology concept (distinct from the pre-Darwinian concept) in the 19th century. Nowadays, however, distinct homology concepts are used in systematics/evolutionary biology, in evolutionary developmental biology, and in molecular biology. The emergence of these different homology concepts is explained as occurring in a rational fashion. The gene case study argues that conceptual progress occurred with the transition from the classical to the molecular gene concept, despite a change in reference. In the last two decades, change occurred internal to the molecular gene concept, so that nowadays this concept's usage and reference varies from context to context. I argue that this situation emerged rationally and that the current variation in usage and reference is conducive to biological practice.The dissertation uses ideas and methodological tools from the philosophy of mind and language, the philosophy of science, the history of science, and the psychology of concepts. (shrink)

Philosophical theories of evidence have been on offer, but they are mostly evaluated in terms of all-or-none desiderata — if they fail to meet one of the desiderata, they are not a satisfactory theory. In this thesis, I aim to accomplish three missions. Firstly, I construct a new way of evaluating theories of evidence, which I call a tool-based view. Secondly, I analyse the nature of what I will call the various relevance-mediating vehicles that each theory of evidence employs. Thirdly, (...) I articulate the comparative core of evidential reasoning in the historical sciences, one which is overlooked in major theories of evidence. On the first mission, I endorse a meta-thesis of pluralism on theories of evidence, namely a tool-based view. I regard a theory of evidence as a purpose-specific and setting-sensitive tool which has its own strengths, difficulties and limitations. Among the major theories of evidence I have reviewed, I focus on Achinstein’s explanationist theory, Cartwright’s argument theory and Reiss’s inferentialist account, scrutinising and evaluating them against the purposes they set out and the scope of their applications. On the second mission, I note that there is no such thing as intrinsically ‘being evidence’. Rather, I hold that relevance-mediating vehicles configure data, materials or claims in such ways that some of them are labelled evidence. I identify the relevance-mediating vehicles that the theories of evidence employ. On the final mission, I argue that the likelihoodist account is an appropriate tool for explaining the evidential reasoning in poorly specified settings where likelihoods can be only imprecisely compared. Such settings, I believe, are typical in the historical sciences. Using the reconstruction of proto-sounds in historical linguistics as a case study, I formalise the rationale behind it by means of the law of likelihood. (shrink)