Recently, some Newton scholars have argued that Newton is an empiricist about metaphysics—that ideally, he wants to let advances in physical theory resolve either some or all metaphysical issues. But while proponents of this interpretation are using ‘metaphysics’ in a very broad sense, to include the ‘principles that enable our knowledge of natural phenomena’, attention has thus far been focused on Newton’s approach to ontological, not epistemological or methodological, issues. In this essay, I therefore consider whether Newton wants to let (...) physical theory bear on the very ‘principles that enable our knowledge’. By examining two kinds of argument in the Principia, I contend that Newton can be considered a methodological empiricist in a substantial respect. I also argue, however, that he cannot be a ‘radical empiricist’—that he does not and cannot convert all methodological issues into empirical issues.Keywords: Newton; Scientific method; Regulæ Philosophandi; Induction; Empiricism. (shrink)

John Norton has proposed a position of “material induction” that denies the existence of a universal inductive inference schema behind scientific reasoning. In this vein, Norton has recently presented a “dome scenario” based on Newtonian physics that, in his understanding, is at variance with Bayesianism. The present note points out that a closer analysis of the dome scenario reveals incompatibilities with material inductivism itself.

Experimental archaeology is often understood both as testing hypotheses about processes shaping the archaeological record and as generating tacit knowledge. Considering lithic technologies, I examine the relationship between these conceptions. Experimental archaeology is usefully understood via “maker’s knowledge”: archaeological experiments generate embodied know-how enabling archaeological hypotheses to be grasped and challenged, and further, well-positioning archaeologists to generate integrated interpretations. Finally, experimental archaeology involves “material speculation”: the constraints and affordances of archaeologists and their materials shape productive exploration of the capacities of (...) objects and human skill in ways relevant to archaeological questions. (shrink)

Despite wide recognition that speculation is critical for successful science, philosophers have attended little to it. When they have, speculation has been characterized in narrowly epistemic terms: a hypothesis is speculative due to its (lack of) evidential support. These ‘evidence-first’ accounts provide little guidance for what makes speculation productive or egregious, nor how to foster the former while avoiding the latter. I examine how scientists discuss speculation and identify various functions speculations play. On this basis, I develop a ‘function-first’ account (...) of speculation. This analysis grounds a richer discussion of when speculation is egregious and when it is productive, based in both fine-grained analysis of the speculation’s purpose, and what I call the ‘epistemic situation’ scientists face. (shrink)

Current philosophical accounts of causation suggest that the same causal assertion can have different meanings. Yet, in actual social-scientific practice, the possible meanings of some causal generalisations intended to support policy prescriptions are not always spelled out. In line with a standard referentialist approach to semantics, we propose and elaborate on four questions to systematically elucidate the meaning of causal generalisations. The analysis can be useful to a host of agents, including social scientists, policy-makers, and philosophers aiming at being socially (...) relevant. To illustrate our proposal, we analyse the complexities related to the meaning of causal generalisations in the context of a concrete case of economic research which is explicitly intended to guide public policy, namely, the OECD research on the causes of unemployment. (shrink)

Economists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case study, three questions are adressed. What are the meanings of causal claims? How can a causal claim be adequately supported by evidence? How are causal beliefs affected by incoming facts? In the process of answering these semantic, (...) epistemic and dynamical questions, the richness of causal reasoning in economics is brought to the foreground. In the part on semantics, it is argued that the meaning of causal generalizations in policy-oriented economics is best captured by using the concept of ‘inferential relation’ rather than the one of ‘referential relation’. This part contributes to develop an inferentialist semantics by distinguishing among types of inferential relations. In the part on epistemology, it is argued that justification in sciences like economics often relies, and ought to rely, on evidential variety―i.e. the combination of evidence from multiple sources. An interpretation of independence among evidential sources is offered: two evidential sources are fully independent if and only if the reasons why they would be unreliable do not overlap. It is then shown that the variety-of-evidence thesis does not hold under extreme circumstances. The part on dynamics focuses on deviant-case study. A storyline is provided for what deviant-case study aims at and how it proceeds in what is characterized as an ‘eclectic science’. (shrink)

The most common way of analysing the meaning of causal generalisations relies on referentialist semantics. In this article, we instead develop an analysis based on inferentialist semantics. According to this approach, the meaning of a causal generalisation is constituted by the web of inferential connections in which the generalisation participates. We distinguish and discuss five classes of inferential connections that constitute the meaning of causal generalisations produced in policy-oriented economic research. The usefulness of our account is illustrated with the analysis (...) of generalisations about unemployment put forward by the Organisation for Economic Co-operation and Development in its highly influential 1994 OECD Jobs Study. The article ends with a discussion of some crucial philosophical questions about the use of inferentialism in the analysis of causal generalisations. (shrink)

In evaluating science, philosophers tends to focus on general laws and on their truth. I urge a shift in focus to the reliability of the panoply of outputs science produces and in tandem, from the general to the particular. Here I give five arguments to support this, including many, many scientific outputs, which must be supposed reliable if we are to warrant our general principles, aren’t truth-apt; and reliability invites the crucial question, ‘Reliable for what?’ Getting clear the particular purpose (...) is essential for effective action and just evaluation. (shrink)

Enhanced indispensability arguments claim that Scientific Realists are committed to the existence of mathematical entities due to their reliance on Inference to the best explanation. Our central question concerns this purported parity of reasoning: do people who defend the EIA make an appropriate use of the resources of Scientific Realism to achieve platonism? We argue that just because a variety of different inferential strategies can be employed by Scientific Realists does not mean that ontological conclusions concerning which things we should (...) be Scientific Realists about are arrived at by any inferential route which eschews causes, and nor is there any direct pressure for Scientific Realists to change their inferential methods. We suggest that in order to maintain inferential parity with Scientific Realism, proponents of EIA need to give details about how and in what way the presence of mathematical entities directly contribute to explanations. (shrink)

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. This approach explains (...) why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

Review essay of The Philosophy of Experimental Biology by Marcel Weber (Cambridge University Press, 2005).

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

Since Krebs and Davies’s (1978) landmark publication, it is acknowledged that behavioural ecology owes much to the ethological tradition in the study of animal behaviour. Although this assumption seems to be right—many of the first behavioural ecologists were trained in departments where ethology developed and matured—it still to be properly assessed. In this paper, I undertake to identify the approaches used by ethologists that contributed to behavioural ecology’s constitution as a field of inquiry. It is my contention that the current (...) practices in behavioural biology owe ethology something much subtler than the simple transposition of Tinbergen’s Four Problems for heuristic purposes. Demonstrating what ethology inherited from the long naturalist tradition shows the tensions that strained the field and that later led to the loss of both its unity and its specificity. It also allows for a precise delineating of what behavioural ecology picked up from the ethological practice, and it helps to cast some light on the introduction of economical thinking in behavioural sciences. (shrink)

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

Empiricists claim that in accepting a scientific theory one should not commit oneself to claims about things that are not observable in the sense of registering on human perceptual systems (according to Van Fraassen’s constructive empiricism) or experimental equipment (according to what I call liberal empiricism ). They also claim scientific theories should be accepted or rejected on the basis of how well they save the phenomena in the sense delivering unified descriptions of natural regularities among things that meet their (...) conditions for observability. I argue that empiricism is both unfaithful to real world scientific practice, and epistemically imprudent, if not incoherent. To illuminate scientific practice and save regularity phenomena one must commit oneself to claims about causal mechanisms that can be detected from data, but do not register directly on human perceptual systems or experimental equipment. I conclude by suggesting that empiricists should relax their standards for acceptable beliefs. (shrink)

Machamer, Darden, and Craver argue that causal explanations explain effects by describing the operations of the mechanisms which produce them. One of this paper’s aims is to take advantage of neglected resources of Mechanism to rethink the traditional idea that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal explanations. I think that causal productivity and regularity are by no means the same thing, (...) and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers’ from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research. (shrink)

This paper aims to advance two claims. First, it aims to show that Hume's argument against the rationality of induction is sound. However, I claim that the conclusion does not follow merely from the self-defeating attempts to justify the rule of induction, unlike traditional readings of the argument. Rather, the skeptical conclusion must also take into account Hume's argument that the secret powers that are present in bodies and give rise to sensible qualities are unknowable. The paper's second aim is (...) to show that Newtonian induction escapes Hume's secret powers argument, given that it includes a transductive inference, from observable phenomena to the powers present in the ultimate parts of matter. Consequently Hume's argument against the rationality of induction does not demonstrate the non-rational nature of Newtonian induction. (shrink)

This paper aims to advance two claims. First, it aims to show that Hume’s argument against the rationality of induction is sound. However, I claim that the conclusion does not follow merely from the self-defeating attempts to justify the rule of induction, unlike traditional readings of the argument. Rather, the skeptical conclusion must also take into account Hume’s argument that the secret powers that are present in bodies and give rise to sensible qualities are unknowable. The paper’s second aim is (...) to show that Newtonian induction escapes Hume’s secret powers argument, given that it includes a transductive inference, from observable phenomena to the powers present in the ultimate parts of matter. Consequently Hume’s argument against the rationality of induction does not demonstrate the non-rational nature of Newtonian induction. (shrink)

This paper discusses recent attempts to solve the problem of induction. Two broad strategies to escape Hume's fork can be distinguished. The first tries to localize the justification of specific inductions in uncontroversial empirical knowledge, e.g.mundane scientific knowledge (J. D. Norton) or perception (M. Lange). I argue that related attempts to (dis)solve the problem fail. The second strategy tries to put forward an argument in favor of induction. As a discussion of work by R. White shows, this argument can barely (...) prove that induction is reliable or at least not unreliable. But D. Steel, F. Huber and G. Schurz could show that enumerative induction is necessary and sufficient for a certain epistemic goal or optimal in a certain sense. These proofs, however, only solve the problem of induction if the goal or a certain standard has priority over the avoidance of error. This suggests that the difficulties to justify induction do not so much derive from Hume's fork, but rather from a plurality of sensible epistemic goals that can conflict with each other. (shrink)

If cosmology is to obtain knowledge about the whole universe, it faces an underdetermination problem: Alternative space-time models are compatible with our evidence. The problem can be avoided though, if there are good reasons to adopt the Cosmological Principle (CP), because, assuming the principle, one can confine oneself to the small class of homogeneous and isotropic space-time models. The aim of this paper is to ask whether there are good reasons to adopt the Cosmological Principle in order to avoid underdetermination (...) in cosmology. Various strategies to justify the CP are examined. For instance, arguments to the effect that the truth of the CP follows generically from a large set of initial conditions; an inference to the best explanation; and an inductive strategy are assessed. I conclude that a convincing justification of the CP has not yet been established, but this claim is contingent on a number of results that may have to be revised in the future. (shrink)

We evaluate a common reasoning strategy used in community ecology and comparative psychology for selecting between competing hypotheses. This strategy labels one hypothesis as a “null” on the grounds of its simplicity and epistemically privileges it as accepted until rejected. We argue that this strategy is unjustified. The asymmetrical treatment of statistical null hypotheses is justified through the experimental and mathematical contexts in which they are used, but these contexts are missing in the case of the “pseudo-null hypotheses” found in (...) our case studies. Moreover, statistical nulls are often not epistemically privileged in practice over their alternatives because failing to reject the null is usually a negative result about the alternative, experimental hypothesis. Scientists should eschew the appeal to pseudo-nulls. It is a rhetorical strategy that glosses over a commitment to valuing simplicity over other epistemic virtues in the name of good scientific and statistical methodology. (shrink)

Scientific realism and anti-realism are most frequently discussed as global theses: theses that apply equally well across the board to all the various sciences. Against this status quo I defend the localist alternative, a methodological stance on scientific realism that approaches debates on realism at the level of individual sciences, rather than at science itself. After identifying the localist view, I provide a number of arguments in its defense, drawing on the diversity and disunity found in the sciences, as well (...) as problems with other approaches (such as basing realism debates on the aim of science). I also show how the view is already at work, explicitly or implicitly, in the work of several philosophers of science. After meeting the objections that localism collapses either into globalism or hyperlocalism, I conclude by sketching what sorts of impacts localism can have in the philosophy of science. (shrink)

En este artículo defiendo que el problema humeano de la justificación racional de la inducción no ha contribuido a la comprensión filosófica de este tipo de inferencias. La teoría material de la inducción propuesta por Norton (2003) permite analizar el razonamiento inductivo más allá del laberinto justificativo humeano, pero con un corte demasiado alto: asumir que las inducciones dependen intrínsecamente de cómo es localmente la realidad. En su lugar, propongo una teoría de la inducción en la que las inducciones dependen (...) no de tesis ontológicas, sino de las capacidades cognitivas para comprimir información de un modo epistémicamente efectivo. (shrink)

Meta-induction, in its various forms, is an imitative prediction method, where the prediction methods and the predictions of other agents are imitated to the extent that those methods or agents have proven successful in the past. In past work, Schurz demonstrated the optimality of meta-induction as a method for predicting unknown events and quantities. However, much recent discussion, along with formal and empirical work, on the Wisdom of Crowds has extolled the virtue of diverse and independent judgment as essential to (...) maintenance of 'wise crowds'. This suggests that meta-inductive prediction methods could undermine the wisdom of the crowd inasmuch these methods recommend that agents imitate the predictions of other agents. In this article, we evaluate meta-inductive methods with a focus on the impact on a group's performance that may result from including meta-inductivists among its members. In addition to considering cases of global accessibility (i.e., cases where the judgments of all members of the group are available to all of the group's members), we consider cases where agents only have access to the judgments of other agents within their own local neighborhoods. (shrink)

Some scientific categories seem to correspond to genuine features of the world and are indispensable for successful science in some domain; in short, they are natural kinds. This book gives a general account of what it is to be a natural kind and puts the account to work illuminating numerous specific examples.

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

In situations where we ignore everything but the space of possibilities, we ought to suspend judgment—that is, remain agnostic—about which of these possibilities is the case. This means that we cannot sum our degrees of belief in different possibilities, something that has been formalized as an axiom of non-additivity. Consistent with this way of representing our ignorance, I defend a doxastic norm that recommends that we should nevertheless follow a certain additivity of possibilities: even if we cannot sum degrees of (...) belief in different possibilities, we should be more confident in larger groups of possibilities. It is thus shown that, in the type of situation considered (in so-called ‘classical ignorance’, i.e. “behind a thin veil of ignorance”), it is epistemically rational for advocates of suspending judgment to endorse this comparative confidence; while on the other hand it is shown that, even in classical ignorance, no stronger belief—such as a precise uniform probability distribution—is warranted. (shrink)

As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments from feminist philosophy of (...) science to machine learning programs to make the case that the resources required to respond to these inductive challenges render critical aspects of their design constitutively value-laden. I demonstrate these points specifically in the case of recidivism algorithms, arguing that contemporary debates concerning fairness in criminal justice risk-assessment programs are best understood as iterations of traditional arguments from inductive risk and demarcation, and thereby establish the value-laden nature of automated decision-making programs. Finally, in light of these points, I address opportunities for relocating the value-free ideal in machine learning and the limitations that accompany them. (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)

Dennett (_Synthese,_ _53_(2), 159–180, 1982, 1991, _Journal of Consciousness Studies,_ _10_(9–10), 19–30, 2003, _Phenomenology and the Cognitive Sciences,_ _6_, 247–270, 2007 ) proposes and defends a method called _heterophenomenology_. Heterophenomenology is a method to study consciousness _from a third-person objective point of view_ as opposed to a first-person subjective point of view or (auto)-phenomenology. The method of heterophenomenology serves a necessary role in Dennett’s schema of bridging the gap between the manifest and the scientific image of the world. In this (...) paper, I attempt to present a limited critique of the method of heterophenomenology. The objection raised in this paper is limited to one of the steps involved in the method, i.e., the interpretation of the heterophenomenological text as analogous to novelist fiction. I attempt to show that the assumptions made by Dennett about the interpretation of fiction are contradictory in nature and therefore the same cannot be applied to the interpretation of a heterophenomenological text. The assumptions fail in justifying the interpretation of fiction itself and hence exporting them by analogy to interpret a heterophenomenological text is a mistake. (shrink)

The justification of induction is of central significance for cross-cultural social epistemology. Different ‘epistemological cultures’ do not only differ in their beliefs, but also in their belief-forming methods and evaluation standards. For an objective comparison of different methods and standards, one needs (meta-)induction over past successes. A notorious obstacle to the problem of justifying induction lies in the fact that the success of object-inductive prediction methods (i.e., methods applied at the level of events) can neither be shown to be universally (...) reliable (Hume's insight) nor to be universally optimal. My proposal towards a solution of the problem of induction is meta-induction. The meta-inductivist applies the principle of induction to all competing prediction methods that are accessible to her. By means of mathematical analysis and computer simulations of prediction games I show that there exist meta-inductive prediction strategies whose success is universally optimal among all accessible prediction strategies, modulo a small short-run loss. The proposed justification of meta-induction is mathematically analytical. It implies, however, an a posteriori justification of object-induction based on the experiences in our world. In the final section I draw conclusions about the significance of meta-induction for the social spread of knowledge and the cultural evolution of cognition, and I relate my results to other simulation results which utilize meta-inductive learning mechanisms. (shrink)

The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a single (...) formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it. Which that is, and its extent, is determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. (shrink)

This book contains a selection of the papers presented at the Logic, Reasoning and Rationality 2010 conference in Ghent. The conference aimed at stimulating the use of formal frameworks to explicate concrete cases of human reasoning, and conversely, to challenge scholars in formal studies by presenting them with interesting new cases of actual reasoning. According to the members of the Wiener Kreis, there was a strong connection between logic, reasoning, and rationality and that human reasoning is rational in so far (...) as it is based on logic. Later, this belief came under attack and logic was deemed inadequate to explicate actual cases of human reasoning. Today, there is a growing interest in reconnecting logic, reasoning and rationality. A central motor for this change was the development of non-classical logics and non-classical formal frameworks. The book contains contributions in various non-classical formal frameworks, case studies that enhance our apprehension of concrete reasoning patterns, and studies of the philosophical implications for our understanding of the notions of rationality. (shrink)

This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in (...) making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research. (shrink)

This undergraduate textbook introduces some fundamental issues in philosophy of science for students of philosophy and science students. The book is divided into two parts. Part 1 deals with knowledge and values. Chap. 1 presents the classical conception of knowledge as initiated by the ancient Greeks and elaborated during the development of science, introducing the central concepts of truth, belief and justification. Aspects of the quest for objectivity are taken up in the following two chapters. Moral issues are broached in (...) Chap. 4, which discusses some aspects of the use and abuse of science, taking up the responsibilities of scientists in properly conducting their business and decision-makers in their concerns with the import of science for society. Part 2 contrasts the view of scientific progress as the rejecting of old hypotheses and theories and replacing them with new ones, represented by Karl Popper, with the conception of progress as accumulating knowledge, saving as much as possible from older theories, represented by Pierre Duhem. A concluding chapter defends the natural attitude of taking the theories of modern science to be literally true, i.e. realism, in the face of arguments drawn partly from the history of scientific progress in criticism of this stance. (shrink)

Our purpose in this paper is to contribute to a practice-based characterization of scientific inference. We want to explore whether Brandom’s pragmatist–inferentialist framework can suitably accommodate several types of ampliative inference common in scientific reasoning and explanation (probabilistic reasoning, abduction and idealisation). First, we argue that Brandom’s view of induction in terms of merely permissive inferences is inadequate; in order to overcome the shortcoming of Brandom’s proposal, we put forward an alternative conception of inductive, probabilistic reasoning by appeal to the (...) notion of degrees of commitment. Moreover, we examine the sorts of inferential commitments operative in other types of ampliative inferences, such as abduction or reasoning involving idealizations and assumptions. We suggest that agents engaging in these forms of reasoning often undertake restricted inferential commitments, whose scope and reach are more limited that in the case of the commitments associated with full beliefs. (shrink)

Archaeological data are shadowy in a number of senses. Not only are they notoriously fragmentary but the conceptual and technical scaffolding on which archaeologists rely to constitute these data as evidence can be as constraining as it is enabling. A recurrent theme in internal archaeological debate is that reliance on sedimented layers of interpretative scaffolding carries the risk that “preunderstandings” configure what archaeologists recognize and record as primary data, and how they interpret it as evidence. The selective and destructive nature (...) of data capture in archeology further suggests that there may be little scope for putting “legacy” data to work in new ways. And yet archaeologists have been strikingly successful in mining old datasets for new insights. I situate these concerns in the broader context of debate about the epistemic standing of the historical sciences, and then consider three strategies by which archaeologists address the challenges posed by legacy data. The first two – secondary retrieval and recontextualization – are a matter of reconfiguring the scaffolding that underpins evidential reasoning. The third turns on redeploying old data in the context of computational models that support the experimental simulation of the cultural systems and contexts under study. (shrink)

The orthodox view of logic takes for granted the central importance of logical principles. Logic, and thus logical reasoning, is to be understood as a system of rules or principles with universal application. Let us call this orthodox view logical generalism. In this paper we argue that logical generalism, whether monist or pluralist, is wrong. We then outline an account of logical consequence in the absence of general logical principles, which we call logical particularism.

The interventionist theory of causation has been advertised as an empirically informed and more nuanced approach to causality than the competing theories. However, previous literature has not yet analyzed the regression discontinuity (hereafter, RD) and the difference-in-differences (hereafter, DD) within an interventionist framework. In this paper, I point out several drawbacks of using the interventionist methodology for justifying the DD and RD designs. However, I argue that the first step towards enhancing our understanding of the DD and RD designs from (...) an interventionist perspective is to take advantage of the assumptions of common trend and continuity. (shrink)

This essay criticizes John Norton's 2010 defense of the thesis that “all induction is local.” Norton's local inductions are bound, if cogent, to involve general principles, and the need to accredit these general principles threatens to lead to all the usual problems associated with the ‘problem of induction’. Norton, in fact, recognizes this threat, but his responses are inadequate. The right response involves not induction but a sophisticated version of hypothetico-deduction. Norton's secondary thesis—that if there is a general account of (...) cogent scientific reasoning, then it is certainly not the one supported by personalist Bayesians—is also criticized. (shrink)

Inferences are familiar movements of thought, but despite important recent work on the topic, we do not yet have a fully satisfying theory of inference. Here I provide a functionalist theory of inference. I argue that the functionalist framework allows us the flexibility to meet various demands on a theory of inference that have been proposed (such as that it must explain inferential Moorean phenomena and epistemological ‘taking’). While also allowing us to compare, contrast, adapt, and combine features of extant (...) theories of inference into one unified theory. In fleshing out the inference role, I also criticize the common assumption that inference requires rule-following. (shrink)

Let us call ‘veridicalism’ the view that perceptual beliefs and observational reports are largely truthful. This paper aims to make a case for veridicalism by, among other things, examining in detail and ultimately deflating in import what many consider to be the view’s greatest threat, the so-called ‘theory-ladenness’ of perception and/or observation. In what follows, it is argued that to the extent that theoretical factors influence the formation of perceptual beliefs and observational reports, as theory-ladenness demands, that influence is typically (...) not detrimental to their veridicality or at least not irreversibly so. Central to the defence of veridicalism are two principles: that of internal similarities and that of internal dissimilarities. (shrink)

In this paper we argue that an existing theory of concepts called dynamic frame theory, although not developed with that purpose in mind, allows for the precise formulation of a number of problems associated with induction from a single instance. A key role is played by the distinction we introduce between complete and incomplete dynamic frames, for incomplete frames seem to be very elegant candidates for the format of the background knowledge used in induction from a single instance. Furthermore, we (...) show how dynamic frame theory provides the terminology to discuss the justification and the fallibility of incomplete frames. In the Appendix, we give a formal account of incomplete frames and the way these lead to induction from a single instance. (shrink)

John D. Norton defends an empiricist epistemology of thought experiments, the central thesis of which is that thought experiments are nothing more than arguments. Philosophers have attempted to provide counterexamples to this claim, but they haven’t convinced Norton. I will point out a more fundamental reason for reformulation that criticizes Norton’s claim that a thought experiment is a good one when its underlying logical form possesses certain desirable properties. I argue that by Norton’s empiricist standards, no thought experiment is ever (...) justified in any deep sense due to the properties of its logical form. Instead, empiricists should consider again the merits of evaluating thought experiments more like laboratory experiments, and less like arguments. (shrink)

European Journal of Philosophy, Volume 29, Issue 4, Page 864-886, December 2021.

This article argues that a successful answer to Hume's problem of induction can be developed from a sub-genre of philosophy of science known as formal learning theory. One of the central concepts of formal learning theory is logical reliability: roughly, a method is logically reliable when it is assured of eventually settling on the truth for every sequence of data that is possible given what we know. I show that the principle of induction (PI) is necessary and sufficient for logical (...) reliability in what I call simple enumerative induction. This answer to Hume's problem rests on interpreting PI as a normative claim justified by a non-empirical epistemic means-ends argument. In such an argument, a rule of inference is shown by mathematical or logical proof to promote a specified epistemic end. Since the proof concerning PI and logical reliability is not based on inductive reasoning, this argument avoids the circularity that Hume argued was inherent in any attempt to justify PI. (shrink)

The no-free-lunch theorems promote a skeptical conclusion that all possible machine learning algorithms equally lack justification. But how could this leave room for a learning theory, that shows that some algorithms are better than others? Drawing parallels to the philosophy of induction, we point out that the no-free-lunch results presuppose a conception of learning algorithms as purely data-driven. On this conception, every algorithm must have an inherent inductive bias, that wants justification. We argue that many standard learning algorithms should rather (...) be understood as model-dependent: in each application they also require for input a model, representing a bias. Generic algorithms themselves, they can be given a model-relative justification. (shrink)