Traditionally, many arguments for realism about properties rely on a priori claims. The author argues that if we make use of an abductive principle that is commonly employed by scientific realists, a new argument for property realism can be formulated which is based firmly in scientific practice. The abductive principle says that we should believe in the existence of certain theoretical entities if they figure in the best explanation for what scientists observe. The scientific argument for property realism then says (...) that the best explanation for various behavioural patterns that physical scientists observe is that microscopic entities instantiate stable, causally efficacious properties. After presenting the argument, the author defends it against possible objections. More generally, the article provides a case study for how science and metaphysics can work together to generate ontological claims. (shrink)

Abduction is considered the most powerful, but also the most controversially discussed type of inference. Based on an analysis of Peirce’s retroduction, Lipton’s Inference to the Best Explanation and other theories, a new theory of abduction is proposed. It considers abduction not as intrinsically explanatory but as intrinsically conditional: for a given fact, abduction allows one to infer a fact that implies it. There are three types of abduction: Selective abduction selects an already known conditional whose consequent is the given (...) fact and infers that its antecedent is true. Conditional-creative abduction creates a new conditional in which the given fact is the consequent and a defined fact is the antecedent that implies the given fact. Propositional-conditional-creative abduction assumes that the given fact is implied by a hitherto undefined fact and thus creates a new conditional with a new proposition as antecedent. The execution of abductive inferences is specified by theory-specific patterns. Each pattern consists of a set of rules for both generating and justifying abductive conclusions and covers the complete inference process. Consequently, abductive inferences can be formalised iff the whole pattern can be formalised. The empirical consistency of the proposed theory is demonstrated by a case study of Semmelweis' research on puerperal fever. (shrink)

The epistemic account and the noetic account hold that the essence of scientific progress is the increase in knowledge and understanding, respectively. Dellsén (2018) criticizes the epistemic account (Park, 2017a) and defends the noetic account (Dellsén, 2016). I argue that Dellsén’s criticisms against the epistemic account fail, and that his notion of understanding, which he claims requires neither belief nor justification, cannot explain scientific progress, although it can explain fictional progress in science-fiction.

L.A. Paul has recently defended the methodology of metaphysics on the grounds that it is continuous with the sciences. She claims that both scientists and metaphysicians use inference to the best explanation to choose between competing theories, and that the success of science vindicates the use of IBE in metaphysics. Specifically, the success of science shows that the theoretical virtues are truth-conducive. I challenge Paul’s claims on two grounds. First, I argue that, at least in biology, scientists adhere to the (...) vera causa ideal, which allows the theoretical virtues to play a much more limited role in scientific reasoning than Paul requires for metaphysical reasoning. The success of biology thus does not vindicate the methodology of metaphysics. Second, I argue that, at least in many cases, the successful reliance on the theoretical virtues in scientific contexts shows only that the theoretical virtues are truth-conducive within those local contexts, and not that they are truth-conducive generally. The upshots are that Paul’s defense of the methodology of metaphysics fails, and that any attempt to rescue her defense must pay more careful attention to what precisely is vindicated by successful science. (shrink)

Despite its profound influence on modern thought, psychoanalysis remains peripheral to the concerns of most analytic philosophers. I suggest that one of the main reasons for this is intellectual reservation, and explore some philosophical arguments against psychoanalysis that may be contributing to such reservation. Specifically, I address the objections that psychoanalytic theories are unfalsifiable, that the purported findings of psychoanalysis are readily explained as due to suggestion, that there is a troubling lack of consensus in psychoanalytic interpretation, and that there (...) is a lack of support for psychoanalysis within mainstream science. I also consider a major obstacle to the acceptance of contemporary defenses of psychoanalysis: the “bad lot” argument against Inference to the Best Explanation. My conclusion is that, though these objections have some merit, they are not sufficient reasons for not taking psychoanalytic ideas seriously. (shrink)

ABSTRACT There is a new argument form within theoretical biology. This form takes as input competing explanatory models; it yields as output the conclusion that one of these models is more plausible than the others. The driving force for this argument form is an analysis showing that one model exhibits more parametric robustness than its competitors. This article examines these inferences to the more robust explanation, analysing them as variants of inference to the best explanation. The article defines parametric robustness (...) and distinguishes it from more familiar kinds of robustness. The article also argues that parametric robustness is an explanatory virtue not subsumed by more familiar explanatory virtues, and that the plausibility verdicts in the conclusions of inferences to the more robust explanations are best interpreted as guidance for research activity, rather than claims about likely truth. 1Introducing Inference to the More Robust Explanation 2Inference to the More Robust Explanation in the Study of Apoptosis 2.1Regulating apoptosis 2.2Competing models and evidential indecision 2.3Measuring robustness 2.4Robustness as a guide to plausibility 2.5Varieties of robustness 3Inference to the More Robust Explanation as Inference to the Best Explanation 3.1The structure of inference to the best explanation 3.2Parametric robustness as an explanatory virtue rather than an explanandum 3.3Relation of parametric robustness to other explanatory virtues 4Epistemological Significance of Inference to the More Robust Explanation 4.1Plausibility in practice 4.2Plausibility in principle 5Conclusion. (shrink)

Associative theories of cognitive representation begin with an ontology of two kinds of entities: concepts and associations. According to most social cognitive theories of attitudes, attitudes are object-evaluation associations of varying strength, where strength is defined in terms of accessibility. This paper proposes a cognitive account of belief such that beliefs are object-attribute associations of varying strength: thus, insofar as evaluative concepts are examples of attribute concepts, attitudes are a species of belief. This cognitive account of belief also denies that (...) additional processes of endorsement—explicit or otherwise—are strictly required for an object-attribute association to count as a belief. (shrink)

We argue that the main results of scientific papers may appropriately be published even if they are false, unjustified, and not believed to be true or justified by their author. To defend this claim we draw upon the literature studying the norms of assertion, and consider how they would apply if one attempted to hold claims made in scientific papers to their strictures, as assertions and discovery claims in scientific papers seem naturally analogous. We first use a case study of (...) William H. Bragg’s early 20th century work in physics to demonstrate that successful science has in fact violated these norms. We then argue that features of the social epistemic arrangement of science which are necessary for its long run success require that we do not hold claims of scientific results to their standards. We end by making a suggestion about the norms that it would be appropriate to hold scientific claims to, along with an explanation of why the social epistemology of science—considered as an instance of collective inquiry—would require such apparently lax norms for claims to be put forward. (shrink)

David Enoch has recently proposed that the deliberative indispensability of irreducibly normative facts suffices to support their inclusion in our ontology, even if they are not necessary for the explanation of any observable phenomena. He challenges dissenters to point to a relevant asymmetry between explanation and deliberation that shows why explanatory indispensability, but not deliberative indispensability, is a legitimate guide to ontology. In this paper, I aim to do just that. Given that an entity figures in the actual explanation of (...) some phenomenon, it is not an open question whether that entity exists. Thus, if you can manage to find actual explanations, you can find answers to ontological questions. In contrast, even if some entity is indispensable to deliberation, it still might not exist. For example, even if some form of libertarian free will is deliberatively indispensable, we still might not have libertarian free will. So even if you manage to discover the indispensable commitments of deliberation, there is still more work to do to get to the bottom of things. That additional work is explanatory work, and so deliberative indispensability is not an independent guide to what there is. (shrink)

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

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

Accounts of modal knowledge are many and varied. How should we choose between them? I propose that we employ inference to the best explanation, and I suggest that there are three desiderata that we should use to rank hypotheses: conservatism, simplicity, and the ability to handle disagreement. After examining these desiderata, I contend that they can’t be used to justify belief in the modal epistemology that fares best, but that they can justify our accepting it in an epistemically significant sense. (...) Finally, I outline a modal epistemology that seems to do well by the standards I’ve recommended. (shrink)

In this paper, I reply to Markus Arnold’s comment and Amanda Bryant’s comment on my work “Can Kuhn’s Taxonomic Incommensurability be an Image of Science?” in Moti Mizrahi’s edited collection, The Kuhnian Image of Science: Time for a Decisive Transformation?. Philosophers and scientists are social epistemic agents. As such, they ought to behave in accordance with epistemic norms governing the behavior of social epistemic agents.

Dawes (2013) claims that we ought not to believe but to accept our best scientific theories. To accept them means to employ them as premises in our reasoning with the goal of attaining knowledge about unobservables. I reply that if we do not believe our best scientific theories, we cannot gain knowledge about unobservables, our opponents might dismiss the predictions derived from them, and we cannot use them to explain phenomena. We commit an unethical speech act when we explain a (...) phenomenon in terms of a theory we do not believe. (shrink)