Scientific models need to be investigated if they are to provide valuable information about the systems they represent. Surprisingly, the epistemological question of what enables this investigation has hardly been investigated. Even authors who consider the inferential role of models as central, like Hughes or Bueno and Colyvan, content themselves with claiming that models contain mathematical resources that provide inferential power. We claim that these notions require further analysis and argue that mathematical formalisms contribute to this (...) class='Hi'>inferential role. We characterize formalisms, illustrate how they extend our mathematical resources, and highlight how distinct formalisms offer various inferential affordances. (shrink)

How do we construct ad hoc concepts, especially those characterised by emergent properties? A reasonable hypothesis, suggested both in psychology and in pragmatics , is that some sort of inferential processing must be involved. I argue that this inferential processing can be accounted for in associative terms. My argument is based on the notion of inference as associative pattern completion based on schemata, with schemata being conceived in turn as patterns of concepts and their relationships. The possible role (...) of conscious attention in inferential processes of this sort is also addressed. (shrink)

We advance a framework for an inferential conception of physical laws, addressing the problem of the application of mathematical structures to the relevant structure of physical domains. Physical laws, we argue, express generalizations that work as rules for deriving physically informative inferences about their target systems, hence guiding us in our interaction with various domains. Our analysis of the application of mathematics to the articulation of physical laws follows a threefold scheme. First, we examine the immersion of the relevant (...) structure of physical domains into mathematical structures. Second, we assess the inferential power of laws resulting from the mathematical formalism employed in the immersion step. And third, we provide a suitable physical interpretation for the extant mathematical structures obtained from the inferential step. We demonstrate that a deflationary, empiricist framework for an inferential conception of physical laws delivers both an understanding of the mathematical character of physical laws, and a way of responding to some of the standard philosophical riddles associated with laws. (shrink)

The entire development of modern logic is characterized by various forms of confrontation of what has come to be called proof theory with what has earned the label of model theory. For a long time the widely accepted view was that while model theory captures directly what logical formalisms are about, proof theory is merely our technical means of getting some incomplete grip on this; but in recent decades the situation has altered. Not only did proof theory expand into new (...) realms, generalizing the concept of proof in various directions; many philosophers also realized that meaning may be seen as primarily consisting in certain rules rather than in language-world links. However, the possibility of construing meaning as an inferential role is often seen as essentially compromised by the limits of prooftheoretical means. The aim of this paper is to sort out the cluster of problems besetting logical inferentialism by disentangling and clarifying one of them, namely determining the power of various inferential frameworks as measured by that of explicitly semantic ones. (shrink)

Reliability theories of epistemic justification face three main objections: the generality problem, the demon-world (or brain-in-a-vat) counterexample, and the clairvoyant-powers counterexample. In Perception and Basic Beliefs(Oxford 2009), Jack Lyons defends reliabilism at length against the clairvoyant powers case. He argues that the problem arises due to a laxity about the category of basic beliefs, and the difference between inferential and non-inferential justification. Lyons argues reliabilists must pay more attention to architecture. I argue this isn’t necessarily so. What really (...) matters for understanding and solving the case involves paying closer attention to the origins of our belief forming capacities, both inferential and non-inferential. Reliabilists should make origins matter more. (shrink)

Among philosophers of science, there is now a widespread agreement that the DN model of explanation is poorly equipped to account for explanations in biology. Rather than identifying laws, so the consensus goes, researchers explain biological capacities by constructing a model of the underlying mechanism.We think that the dichotomy between DN explanations and mechanistic explanations is misleading. In this article, we argue that there are cases in which biological capacities are explained without constructing a model of the underlying mechanism. Although (...) these explanations do not conform to Hempel’s DN model, they do invoke more or less stable generalisations. Because they invoke generalisations and have the form of an argument, we call them inferential explanations. We support this claim by considering two examples of explanations of biological capacities: pigeon navigation and photoperiodism. Next, we will argue that these non-mechanistic explanations are crucial to biology in three ways: sometimes, they are the only thing we have, they are heuristically useful, and they provide genuine understanding and so are interesting in their own right.In the last sections we discuss the relation between types of explanations and types of experiments and situate our views within some relevant debates on explanatory power and explanatory virtues. (shrink)

Inferential statistical tests-such as analysis of variance, t-tests, chi-square and Wilcoxin signed ranks-now constitute a principal class of methods for the testing of scientific hypotheses. In this paper I will consider the role of one statistical concept (statistical power) and two statistical principles or assumptions (homogeneity of variance and the independence of random error), in the reliable application of selected statistical methods. I defend a tacit but widely-deployed naturalistic principle of explanation (E): Philosophers should not treat as inexplicable (...) or basic those correlational facts that scientists themselves do not treat as irreducible. In light of (E), I contend that the conformity of epistemically reliable statistical tests to these concepts and assumptions entails at least the following modest or austere realist commitment: (C) The populations under study have a stable theoretical or unobserved structure that metaphysically grounds the observed values; the objects therefore have a fixed value independent of our efforts to measure them. (C) provides the best explanation for the correlation between the joint use of statistical assumptions and statistical tests, on the one hand, and methodological success on the other. (shrink)

Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual (...) approach to explanation and the view of understanding as an inferential ability. By combining these perspectives, we show how the explanatory power of an explanation in a given dimension can be assessed by showing the range of answers it provides to what-if-things-had-been-different questions and the theoretical and pragmatic importance of these questions. Our account also explains intuitions linking explanation to unification or to exhibition of a mechanism. (shrink)

In this article we defend the inferential view of scientific models and idealisation. Models are seen as “inferential prostheses” (instruments for surrogative reasoning) construed by means of an idealisation-concretisation process, which we essentially understand as a kind of counterfactual deformation procedure (also analysed in inferential terms). The value of scientific representation is understood in terms not only of the success of the inferential outcomes arrived at with its help, but also of the heuristic power of (...) representation and their capacity to correct and improve our models. This provides us with an argument against Sugden’s account of credible models: the likelihood or realisticness (their “credibility”) is not always a good measure of their acceptability. As opposed to “credibility” we propose the notion of “enlightening”, which is the capacity of giving us understanding in the sense of an inferential ability. (shrink)

In this article we defend the inferential view of scientific models and idealisation. Models are seen as “inferential prostheses” (instruments for surrogative reasoning) construed by means of an idealisation-concretisation process, which we essentially understand as a kind of counterfactual deformation procedure (also analysed in inferential terms). The value of scientific representation is understood in terms not only of the success of the inferential outcomes arrived at with its help, but also of the heuristic power of (...) representation and their capacity to correct and improve our models. This provides us with an argument against Sugden’s account of credible models: the likelihood or realisticness (their “credibility”) is not always a good measure of their acceptability. As opposed to “credibility” we propose the notion of “enlightening”, which is the capacity of giving us understanding in the sense of an inferential ability. (shrink)

In this article we defend the inferential view of scientific models and idealisation. Models are seen as “inferential prostheses” (instruments for surrogative reasoning) construed by means of an idealisation-concretisation process, which we essentially understand as a kind of counterfactual deformation procedure (also analysed in inferential terms). The value of scientific representation is understood in terms not only of the success of the inferential outcomes arrived at with its help, but also of the heuristic power of (...) representation and their capacity to correct and improve our models. This provides us with an argument against Sugden’s account of credible models: the likelihood or realisticness (their “credibility”) is not always a good measure of their acceptability. As opposed to “credibility” we propose the notion of “enlightening”, which is the capacity of giving us understanding in the sense of an inferential ability. (shrink)

There is no consensus as to whether a Liar sentence is meaningful or not. Still, a widespread conviction with respect to Liar sentences (and other ungrounded sentences) is that, whether or not they are meaningful, they are useless . The philosophical contribution of this paper is to put this conviction into question. Using the framework of assertoric semantics , which is a semantic valuation method for languages of self-referential truth that has been developed by the author, we show that certain (...) computational problems, called query structures , can be solved more efficiently by an agent who has self-referential resources (amongst which are Liar sentences) than by an agent who has only classical resources; we establish the computational power of self-referential truth . The paper concludes with some thoughts on the implications of the established result for deflationary accounts of truth. (shrink)

I argue that mathematical representations can have heuristic power since their construction can be ampliative. To this end, I examine how a representation introduces elements and properties into the represented object that it does not contain at the beginning of its construction, and how it guides the manipulations of the represented object in ways that restructure its components by gradually adding new pieces of information to produce a hypothesis in order to solve a problem.In addition, I defend an ‘ (...) class='Hi'>inferential’ approach to the heuristic power of representations by arguing that these representations draw on ampliative inferences such as analogies and inductions. In effect, in order to construct a representation, we have to ‘assimilate’ diverse things, and this requires identifying similarities between them. These similarities form the basis for ampliative inferences that gradually build hypotheses to solve a problem.To support my thesis, I analyse two examples. The first one is intra-field, that is, the construction of an algebraic representation of 3-manifolds; the second is inter-fields, that is, the construction of a topological representation of DNA supercoiling. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Semantic Powers: Meaning and the Means of Knowing in Classical Indian PhilosophyHarold CowardSemantic Powers: Meaning and the Means of Knowing in Classical Indian Philosophy. By Jonardon Ganeri. Oxford: Oxford University Press, 1999. Pp. x + 266.In Semantic Powers: Meaning and the Means of Knowing in Classical Indian Philosophy, Jonardon Ganeri adds to our understanding of the Nyāya philosophy of language in the modern English-speaking world. Building on Bimal (...) Matilal's introduction to Nyāya thought in Matilal's foundational Epistemology Logic and Grammar in Indian Philosophical Analysis (1971) and on Karl Potter and Sibajiban Bhattacharyya's Nyāya-Vaiśeṣika from Gangeśa to Raghunatha Siromani (1993), Ganeri's clearly written book valuably extends our knowledge of the Nyāya philosophy of language by its exposition of the seventeenth-century Nyāya philosopher Gadādhara's Saktivāda or "Essay on Semantic Power." Ganeri's exposition is based on having read the first half of the Saktivāda text with Matilal, before the latter's untimely death, and the second half with Bhattacharyya in Calcutta.In the Saktivāda, Gadādhara defends key Nyāya claims as to how language conveys meaning. In the first half of the text, the author deals with such questions as whether languages are convention-based, whether the central function of language is as an instrument of knowing, whether word meaning or sentence meaning is conceptually prior, and whether the notion of meaning is reducible to physical and/or psychological concepts. In the second half, Gadādhara looks at the semantic problems connected with particular constructions: notably proper and theoretical names, anaphors, indexicals, and the quantifiers. The English exposition of Gadādhara's text offered by Ganeri in this book covers the same topics.According to Gadādhara and the Nyāya philosophy, "the language faculty is a sui generis epistemic faculty, reducible to neither perception nor inference nor some combination of these two. The question for the Naiyāyika is: what properties must the language faculty have if it is in this way to be a source of knowledge?" (p. 15). The Nyāya approach also places an emphasis on testimony as a valid source of knowledge (pramāna), which it understands simply as the transmission by language of knowledge from the speaker to the hearer. The "Communication-intention" variable, discussed by recent thinkers such as McDowell, is not dealt with by Nyāya thinkers, who would deny that the acquisition of knowledge by testimony involves anything like the recognition of the speaker's intentions. Rather, the Nyāya thesis is "that understanding typically consists in direct, non-inferential assent, is in sharp contrast to the assumption implicit in McDowell's position: that assenting to another's utterance is never direct, but always depends on the speaker's intentions, or of the speech-act performed by the speaker" (p. 17). In supporting the Nyāya position, Ganeri appeals to Frege's theory of understanding.The basic idea in the Nyāya philosophy of language is that each of us is endowed with a language faculty, analogous to our perceptual faculty, which generates beliefs from perceived utterances. It has a meaning function. As Ganeri puts it: [End Page 419]My testimonial faculty fixes, as it were, a mapping from utterances of a given language to belief contents. The 'meaning' of a statement for me is, by definition, the belief content to which it is mapped by my testimony faculty. If I am able to understand every statement I hear, the language processing mechanism which underpins this faculty must have a certain compositional structure, and that leads to an assignment of belief-content components to subsequential elements in the language, (p. 29)This thought of Gadādhara, dating from about 1700 C.E., resonates with Chomsky's contemporary ideas of "deep structure" and, in classical Indian philosophy, with Bhartṛhari's fifth-century notion of innate-structuring ideas within consciousness (see Coward and Raja, Encyclopedia of Indian Philosophies, vol. 5). Like Bhartṛhari, Gadādhara takes the sentence to be the irreducible meaning-bearing unit of language.While Karl Potter and Sibajiban Bhattacharyya's volume 6 of The Encyclopedia... (shrink)

This paper examines two alleged limitations in the use of formal languages: on the one hand, the trade-offs between expressive and inferential power, and on the other, the phenomenon of system imprisonment. After reconceptualizing the issue, we consider the role played by modality in the understanding of certain aspects of mathematical structures and argue for its centrality.

This study aims to clarify the role played by higher order dispositions in the context of the explanatory method in Regimen I and of the approach to dietetics in Regimen as a whole. My main claim is that there are two concomitant directions involved in the inquiry carried out in Chaps 25–36 of Regimen I: there is an inferential and revelatory move from premises about complex dispositions to the ‘invisible’, that is, to the particular composition of one's body ; (...) and there is a causal-explanatory move, based on such inferences, from the powers of elemental varieties and of their combinations to the resulting higher level dispositions. (shrink)

Language matters to feminism because language is a structure of significances that governs our lives. It contains and conveys the categories through which we understand ourselves and others, and through which we become who and what we are. Our linguistic practices are constituted largely by inferences which in turn constitute or contribute to our understanding of the connections (causal and otherwise) between things. These inferential roles and patterns, which are normatively inscribed, give order and significance to the categories. Once (...) we realize that our linguistic categories reflect and are reflected by our social categories, and once we see that our discursive practices are normative, it is a short step to see language as an arena of political struggle. Feminism is, at the very least, a struggle to end sexist oppression by eradicating both the means by which oppression is carried out and the ideology that seeks that it be carried out. As our most powerful and yet nuanced symbol system, language is perhaps the primary means by which the ideology of sexism is developed and reinforced; it is not news that language is an instrument of oppression. A narrow focus on sexist semantics is of limited use to feminist philosophers, for at best such studies yield lists of past and present harms, with little more to add than “stop it, now.” The real promise of philosophy of language for feminists is an understanding of articulated normativity; by understanding how language really works, we might just understand how the rabbit of normativity gets pulled from the hat of articulation. Language is normative in its production and reproduction of social norms by way of its content, by way of its forms, and most especially by way of its constitutive discursive practices. Once we understand how women are paradoxically constituted by and yet erased from discourse, we may use what we know of these processes of articulation and legitimation to effect and explain our reconstitution as whole. (shrink)

This book presents an in-depth and critical reconstruction of Prawitz’s epistemic grounding, and discusses it within the broader field of proof-theoretic semantics. The theory of grounds is also provided with a formal framework, through which several relevant results are proved. Investigating Prawitz’s theory of grounds, this work answers one of the most fundamental questions in logic: why and how do some inferences have the epistemic power to compel us to accept their conclusion, if we have accepted their premises? Prawitz (...) proposes an innovative description of inferential acts, as applications of constructive operations on grounds for the premises, yielding a ground for the conclusion. The book is divided into three parts. In the first, the author discusses the reasons that have led Prawitz to abandon his previous semantics of valid arguments and proofs. The second part presents Prawitz’s grounding as found in his ground-theoretic papers. Finally, in the third part, a formal apparatus is developed, consisting of a class of languages whose terms are equipped with denotation functions associating them to operations and grounds, as well as of a class of systems where important properties of the terms can be proved. (shrink)

Many systems of logic diagrams have been offered both historically and more recently. Each of them has clear limitations. An original alternative system is offered here. It is simpler, more natural, and more expressively and inferentially powerful. It can be used to analyze not only syllogisms but arguments involving relational terms and unanalyzed statement terms.

Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments (...) or simulations, per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive. (shrink)

This volume on the semantic complexity of natural language explores the question why some sentences are more difficult than others. While doing so, it lays the groundwork for extending semantic theory with computational and cognitive aspects by combining linguistics and logic with computations and cognition. -/- Quantifier expressions occur whenever we describe the world and communicate about it. Generalized quantifier theory is therefore one of the basic tools of linguistics today, studying the possible meanings and the inferential power (...) of quantifier expressions by logical means. The classic version was developed in the 1980s, at the interface of linguistics, mathematics and philosophy. Before this volume, advances in "classic" generalized quantifier theory mainly focused on logical questions and their applications to linguistics, this volume adds a computational component, the third pillar of language use and logical activity. This book is essential reading for researchers in linguistics, philosophy, cognitive science, logic, AI, and computer science. (shrink)

A recent series of experiments have demonstrated that a classical fluid mechanical system, constituted by an oil droplet bouncing on a vibrating fluid surface, can be induced to display a number of behaviours previously considered to be distinctly quantum. To explain this correspondence it has been suggested that the fluid mechanical system provides a single-particle classical model of de Broglie’s idiosyncratic ‘double solution’ pilot wave theory of quantum mechanics. In this paper we assess the epistemic function of the bouncing oil (...) droplet experiments in relation to quantum mechanics. We find that the bouncing oil droplets are best conceived as an analogue illustration of quantum phenomena, rather than an analogue simulation, and, furthermore, that their epistemic value should be understood in terms of how-possibly explanation, rather than confirmation. Analogue illustration, unlike analogue simulation, is not a form of ‘material surrogacy’, in which source empirical phenomena in a system of one kind can be understood as ‘standing in for’ target phenomena in a system of another kind. Rather, analogue illustration leverages a correspondence between certain empirical phenomena displayed by a source system and aspects of the ontology of a target system. On the one hand, this limits the potential inferential power of analogue illustrations, but, on the other, it widens their potential inferential scope. In particular, through analogue illustration we can learn, in the sense of gaining how-possibly understanding, about the putative ontology of a target system via an experiment. As such, the potential scientific value of these extraordinary experiments is undoubtedly a significant one. (shrink)

This thesis investigates two main issues concerning the behavior of rational agents, preference dynamics and agent diversity. -/- We take up two questions left aside by von Wright, and later also the multitude of his successors, in his seminal book Logic of Preference in 1963: reasons for preference, and changes in preference. Various notions of preference are discussed, compared and further correlated in the thesis. In particular, we concentrate on extrinsic preference. Contrary to intrinsic preference, extrinsic preference is reason-based, i.e. (...) one's preference for one option over another has a reason. A logical model is proposed and its properties are determined. Dynamics come in naturally, since reasons for the preferences can change. Logical systems and formal results regarding dynamical preference change are then presented. -/- Preference arises from comparisons between alternatives. A first option is to compare situations. Abstractly speaking, preferences are in this case between propositions, viewed as sets of possible worlds. The reasons can then be based on a `betterness' relation over possible worlds. Propositional preference arises as a lift from this primitive relation. A standard modal logical approach is taken and we use a modality for the betterness relation in the language. We then model preference change by techniques from dynamic epistemic logic (DEL), where a typical action, e.g. a suggestion or a command can change the betterness ordering of the worlds, and thereby the propositional preference. Dynamic reduction axioms are obtained to encode exactly how such a change takes place. We obtain a complete dynamic preference logic. -/- A second option is to compare objects as such. Concretely, properties of the objects often determine the preference over the objects. Properties are now the reasons. Inspired by Optimality Theory (OT), we propose a priority sequence, an ordering of properties. Various ways of getting a preference from the priority sequence are investigated, though we mostly follow the OT approach. We use a fragment of first-order logic to describe the situation. Here, on the dynamic side, it is priority change that leads to preference change. Using the DEL methodology again we propose a complete set of reduction axioms concerning the possible dynamic operations on priority sequences. -/- Not surprisingly, the above two views are closely related. After all, possible worlds can be thought of as objects! On the basis of a systematic comparison of the two views, we develop a two level perspective, in which the models themselves are structured in layers. In particular, correspondence results between the changes at the level of the possible worlds and the changes at the level of the priority sequences are proved. We end up by sketching a two-level preferential predicate logic to describe more complex circumstances in which situations and objects are compared simultaneously. -/- But we do not see this as the whole story. Preference does not live by itself, it is often intermingled with epistemic notions of knowledge and belief. One can have different intuitions about how this entanglement operates. A few options are discussed, and proposals for logical models are presented. When moving to dynamics, we now see a picture of knowledge update, belief revision and preference change taking place symbiotically, often unconsciously as in real life. -/- The resulting picture in the thesis is one of agents that process information and adjust beliefs and preferences in many different ways. There is no logically prescribed unique norm for doing this. The second part of the thesis takes this general phenomenon of diversity of agents as its focus, since it raises many issues for logical systems and the idealized agents which they normally presuppose. In reality, agents can differ across a wide spectrum of cognitive abilities and habits: in their memory capacity, observation power, inferential power, introspective ability, and revision policies when facing new information. -/- Two kinds of agents, perfect recall agents, and memory-free agents are studied thoroughly, in the setting of playing games. We show how current dynamic logics can be `parametrized' to allow for this memory diversity, with new characterizations of agent types resulting in complete dynamic-epistemic logics. The other dimension of the reality of diverse agents is that, however different they are, they often do manage to coordinate with each other successfully. While this theme has been prominent in game theory and multi-agent systems, it has received hardly any attention in logic. We analyze this interaction between different agents by looking at concrete scenarios which model their types explicitly. -/- Finally, we analyze the issue of agent diversity in its generality, discussing what dynamic logics would have to look like to become a full-fledged account of agents of different capacities and tendencies that pursue and sometimes achieve their goals in irreducibly social settings. -/- . (shrink)

In this paper we address the classical but still pending question regarding Thought Experiments: how can an imagined scenario bring new information or insight about the actual world? Our claim is that this general problem actually embraces two distinct questions: how can the creation of a just imagined scenario become functional to either a scientific or a philosophical research? and how can Thought Experiments hold a strong inferential power if their structures “do not seem to translate easily into (...) standard forms of deduction or induction”? :534–541, 1999). We contend that, in order to answer both questions, we should consider the relation between the creation of the imagined scenario and the inferential power of Thought Experiments. Specifically, we will analyze Thought Experiments from an eco-cognitive point of view as goal-oriented objects, explaining their inferential power considering their generation as the result of abductive cognition and the construction of an imagined scenario as a process of scientific modeling. This will lead us to consider the creation of a Thought Experiment as a case of sophisticated model-based abduction. (shrink)

We present an informational view of classical propositional logic that stems from a kind of informational semantics whereby the meaning of a logical operator is specified solely in terms of the information that is actually possessed by an agent. In this view the inferential power of logical agents is naturally bounded by their limited capability of manipulating “virtual information”, namely information that is not implicitly contained in the data. Although this informational semantics cannot be expressed by any finitely-valued (...) matrix, it can be expressed by a non-deterministic 3-valued matrix that was first introduced by W.V.O. Quine, but ignored by the logical community. Within the general framework presented in [21] we provide an in-depth discussion of this informational semantics and a detailed analysis of a specific infinite hierarchy of tractable approximations to classical propositional logic that is based on it. This hierarchy can be used to model the inferential power of resource-bounded agents and admits of a uniform proof-theoretical characterization that is half-way between a classical version of Natural Deduction and the method of semantic tableaux. (shrink)

In recent years, multivariate pattern analysis has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging, electroencephalography, and other neuroimaging methodologies. In a similar time frame, “deep learning” has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques (...) based on linear calculations; a number of studies have applied deep learning techniques to neuroimaging data, but we believe that those have barely scratched the surface of the potential deep learning holds for the field. In this paper, we provide a brief introduction to deep learning for those new to the technique, explore the logistical pros and cons of using deep learning to analyze neuroimaging data – which we term “deep MVPA,” or dMVPA – and introduce a new software toolbox intended to facilitate dMVPA for neuroscientists everywhere. (shrink)

Factual statements that might qualify for the status of law statements are classed from various philosophically relevant standpoints (referents, precision, structure of predicates, extension, systemicity, inferential power, inception, ostensiveness, testability, levels, and determination categories). More than seven dozen of not mutually exclusive kinds of lawlike statements emerge. Strictly universal and counterfactually powerful statements are seen to constitute just one kind of lawlike statements; classificatory and some statistical laws, e.g., are shown not to comply with the requirements of universality (...) and counterfactual force. Conditions for lawlike statements to be called laws are then examined, and a liberal criterion of lawfulness is finally proposed, which reads thus: A proposition is a law statement if and only if it is a posteriori (not logically true), general in some respect (does not refer to unique objects), has been satisfactorily corroborated for the time being in some domain, and belongs to a theory (whether adult or embryonic). It is claimed that criteria of laws change alongside with the emergence of new usages of the term 'law', and that by adopting a liberal criterion of lawfulness we would conform to contemporary usage and would cease inhibiting the search for regularities in the sciences of man. (shrink)

Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to the dominant (...) paradigm for assessing the rationality of actions and decisions, our present evaluation complements our previous work, since our previous evaluation may have been too severe in its assessment of inferences to false and uninformative conclusions. In the end, our new results provide additional support for the conclusion that (of the four systems considered) inference by system Z offers the best balance of error avoidance and inferential power. Our new results also suggest that improved performance could be achieved by a modest strengthening of system Z. (shrink)

In this paper, I stress the utility of employing test-driven development (TDD) for conceiving logical systems. TDD, originally invented in the context of Extreme Programming, is a methodology widely used by software engineers to conceive and develop programs. Its main principle is to design the tests of the expected properties of the system before the development phase. I argue that this methodology is especially convenient in conceiving applied logics. Indeed, this technique is efficient with most decidable logics having a software (...) implementation. Having a clear list of the desired inferences right from the beginning makes it possible to refine the properties of the system step by step until its completion. I distinguish and detail seven advantages of the usage of TDD for the conception of a logical theory. Most importantly, this methodology increases the predictability of the inferential power of the theory. A second important benefit is that the time required for the conception of the logic goes down dramatically. This methodology will change both ideas and practices. Logic is no longer considered to be a formal science, but rather to be an empirical one. Research in the field is geared toward specific and concrete goals. Programs are considered tools used to verify the conformity of formal theories. To sum up, I defend the view that, in some situations, this way of designing a formal system brings significant benefits, and that the construction of new logics can be conducted similarly to the development of open source software. (shrink)

The reduction of grounding to causation, or each to a more general relation of which they are species, has sometimes been justified by the impressive inferential capacity of structural equation modelling, causal Bayes nets, and interventionist causal modelling. Many criticisms of this assimilation focus on how causation is inadequate for grounding. Here, I examine the other direction: how treating grounding in the image of causation makes the resulting view worse for causation. The distinctive features of causal modelling that make (...) this connection appealing are distorted beyond use by forcing them to fit onto grounding. The very inferential strength that makes causation attractive is only possible because of a narrow construal of what counts as a causal relation; as soon as that broadens, the inferential capacity markedly diminishes. Making causation suitable for application to grounding spoils what was appealing about causation for this task in the first place. However, grounding need not appeal to causation: causal modelling does not have exclusive claim to structural equation modeling or other formal techniques of modelling structure. I offer a case in favour of a different kind of metaphysical frugality, which tend towards narrow, more restrictive construals of relations like causation or grounding, because then each relation behaves more homogenously. This more homogenous behavior delivers stronger inferential power per relation even though there may be more relations to which one is committed. (shrink)

In this paper I will defend a new account of scientific representation. I will begin by looking at the benefits and drawbacks of two recent accounts on scientific representation: Hughes’ DDI account and Suárez’ inferential account. Next I use some of Galileo’s models in the Discorsi as a heuristic tool for a better account of scientific representation. Next I will present my model. The main idea of my account, which I refer to as the pragmatic model of shared characteristics (...) (PMSC), is that a model represents, if and only if, (1) a person accepts that there is a set of shared characteristics between the model and its target; (2) this set has the inferential power to generate results which can be tested empirically; (3) and the corresponding test(s) of these results is/are in agreement with our data and the specific cognitive goals we have in mind. (shrink)

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive action explanation has (...) a modal strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt. (shrink)

Definitions are traditionally seen as abbreviations, as tools for notational convenience that do not increase inferential power. From a Philosophy of Mathematical Practice point of view, however, there is much more to definitions. For example, definitions can play a role in problem solving, definitions can contribute to understanding, sometimes equivalent definitions are appreciated differently, and so on. This chapter reviews the literature on definitions and (to a certain extent) concepts in mathematical practice. It is structured according to four (...) themes through which definitions (and concepts) in mathematical practice have been studied. These themes concern (1) the nature of definitions, (2) whether and how concepts evolve, (3) definitions and concepts from a communal perspective, and (4) different values relating to definitions and concepts. (shrink)

Some of the concerns people have about AI are: its misuses, effect on unemployment, and its potential for dehumanising. Contrary to what most people believe and fear, AI can lead to respect for the enormous power and complexity of the human mind. It is potentially very dangerous for users in the public domain to impute much more inferential power to computer systems, which look common-sensical, than they actually have. No matter how impressive AI programs may be, we (...) must be aware of their limitations and should not abrogate human responsibility to such programs. (shrink)

Our aim is to model the behaviour of a cognitive agent trying to solve a complex problem by dividing it into sub-problems, but failing to solve some of these sub-problems. We use the powerful framework of erotetic search scenarios combined with Kleene’s strong three-valued logic. ESS, defined on the grounds of Inferential Erotetic Logic, has appeared to be a useful logical tool for modelling cognitive goal-directed processes. Using the logical tools of ESS and the three-valued logic, we will show (...) how an agent could solve the initial problem despite the fact that the sub-problems remain unsolved. Thus our model not only indicates missing information but also specifies the contexts in which the problem-solving process may end in success despite the lack of information. We will also show that this model of problem solving may find use in an analysis of natural language dialogues. (shrink)

The power PC theory postulates a normative procedure for making causal inferences from contingency information, and offers this as a descriptive model of human causal judgement. The inferential procedure requires a set of assumptions, which includes the assumption that the cause being judged is distributed independently of the set of other possible causes of the same outcome. It is argued that this assumption either never holds or can never be known to hold. It is also argued that conformity (...) of judgements to the prescriptions of the model requires a sophisticated appreciation of methodological factors and acquired domain-specific knowledge of causes, and that the theory is disconfirmed by a finding that an objective contingency that equally supports two causal inferences results in only one of them actually being made. An alternative proposal based on the hypothesis that causal understanding originates with experiences of forces exerted while acting on objects is briefly sketched. (shrink)

The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate (...) that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system. (shrink)

Open-minded people should endorse dogmatism because of its explanatory power. Dogmatism holds that, in the absence of defeaters, a seeming that P necessarily provides non-inferential justification for P. I show that dogmatism provides an intuitive explanation of four issues concerning non-inferential justification. It is particularly impressive that dogmatism can explain these issues because prominent epistemologists have argued that it can’t address at least two of them. Prominent epistemologists also object that dogmatism is absurdly permissive because it allows (...) a seeming to provide justification even if the seeming was caused in some apparently inappropriate way. I conclude by disarming this objection. (shrink)

DOI: 10.1080/00031305.2018.1564697 When the editors of Basic and Applied Social Psychology effectively banned the use of null hypothesis significance testing (NHST) from articles published in their journal, it set off a fire-storm of discussions both supporting the decision and defending the utility of NHST in scientific research. At the heart of NHST is the p-value which is the probability of obtaining an effect equal to or more extreme than the one observed in the sample data, given the null hypothesis and (...) other model assumptions. Although this is conceptually different from the probability of the null hypothesis being true, given the sample, p-values nonetheless can provide evidential information, toward making an inference about a parameter. Applying a 10,000-case simulation described in this article, the authors found that p-values’ inferential signals to either reject or not reject a null hypothesis about the mean (α = 0.05) were consistent for almost 70% of the cases with the parameter’s true location for the sampled-from population. Success increases if a hybrid decision criterion, minimum effect size plus p-value (MESP), is used. Here, rejecting the null also requires the difference of the observed statistic from the exact null to be meaningfully large or practically significant, in the researcher’s judgment and experience. The simulation compares performances of several methods: from p-value and/or effect size-based, to confidence-interval based, under various conditions of true location of the mean, test power, and comparative sizes of the meaningful distance and population variability. For any inference procedure that outputs a binary indicator, like flagging whether a p-value is significant, the output of one single experiment is not sufficient evidence for a definitive conclusion. Yet, if a tool like MESP generates a relatively reliable signal and is used knowledgeably as part of a research process, it can provide useful information. (shrink)

Based on a typology of five basic forms of abduction, I propose a new definition of abductive insight that empha sizes in particular the inferential structure of a belief system that is able to explain a phenomenon after a new, abductive ly created component has been added to this system or the entire system has been abductively restructured. My thesis is, first, that the argumentative structure of the pursued problem solution guides abductive creativity and, second, that diagrammatic reasoning—if conceptualized (...) according to the requirements defined by Charles Peirce—can support this guidance. This support is mainly possible based on the normative power of the system of representation that has to be used to construct diagrams and to perform experiments with them. (shrink)

One of the most pressing issues in understanding abduction is whether it is an instinct or an inference. For many commentators find it paradoxical that new ideas are products of an instinct and products of an inference at the same time. Fortunately, Lorenzo Magnani’s recent discussion of animal abduction sheds light on both instinctual and inferential character of Peircean abduction. But, exactly for what reasons are Peirce and Magnani so convinced that animal abduction can provide us with a novel (...) perspective? Inspired by Peirce’s and Magnani’s discussions of animal abduction, I propose to compare Peirce’s and Magnani’s views of animal abduction with the estimative power of non-human animals and humans, which was one of the internal senses in medieval psychology. (shrink)

In this paper, I use the predictive processing theory of perception to tackle the question of how perceptual states can be rationally involved in cognition by justifying other mental states. I put forward two claims regarding the epistemological implications of PP. First, perceptual states can confer justification on other mental states because the perceptual states are themselves rationally acquired. Second, despite being inferentially justified rather than epistemically basic, perceptual states can still be epistemically responsive to the mind-independent world. My main (...) goal is to elucidate the epistemology of perception already implicit in PP. But I also hope to show how it is possible to peacefully combine central tenets of foundationalist and coherentist accounts of the rational powers of perception while avoiding the well-recognized pitfalls of either. (shrink)

In this paper, we consider the straw man fallacy from the perspective of pragmatic inference. Our main claim is that the straw man fallacy is a ‘pragmatic winner’ not primarily because of its persuasive power but rather because it targets the pragmatic cognitive-inferential skills of its victim while enhancing the prestige of its author. We consider that in the context of a straw man fallacy, the issue of the burden of proof, which is ‘reversed’, does not directly bear (...) on the argumentation itself but has essentially to do with the difficulty for the targeted speaker of getting the attention of the audience back. It is difficult because countering this fallacy involves primarily a discussion of the reasons why the inference drawn was unduly derived, a process which is virtually destined to be a failure first of all because of the lack of relevance of justifications in comparison with that of actual points. Notions of retractability and the explicit-implicit divide are central to our approach. (shrink)

Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error (...) probabilities is to ensure that only statistical hypotheses that have passed severe or probative tests are inferred from the data. The severity criterion supplies a meta-statistical principle for evaluating proposed statistical inferences, avoiding classic fallacies from tests that are overly sensitive, as well as those not sensitive enough to particular errors and discrepancies. Introduction and overview 1.1 Behavioristic and inferential rationales for Neyman–Pearson (N–P) tests 1.2 Severity rationale: induction as severe testing 1.3 Severity as a meta-statistical concept: three required restrictions on the N–P paradigm Error statistical tests from the severity perspective 2.1 N–P test T(): type I, II error probabilities and power 2.2 Specifying test T() using p-values Neyman's post-data use of power 3.1 Neyman: does failure to reject H warrant confirming H? Severe testing as a basic concept for an adequate post-data inference 4.1 The severity interpretation of acceptance (SIA) for test T() 4.2 The fallacy of acceptance (i.e., an insignificant difference): Ms Rosy 4.3 Severity and power Fallacy of rejection: statistical vs. substantive significance 5.1 Taking a rejection of H0 as evidence for a substantive claim or theory 5.2 A statistically significant difference from H0 may fail to indicate a substantively important magnitude 5.3 Principle for the severity interpretation of a rejection (SIR) 5.4 Comparing significant results with different sample sizes in T(): large n problem 5.5 General testing rules for T(), using the severe testing concept The severe testing concept and confidence intervals 6.1 Dualities between one and two-sided intervals and tests 6.2 Avoiding shortcomings of confidence intervals Beyond the N–P paradigm: pure significance, and misspecification tests Concluding comments: have we shown severity to be a basic concept in a N–P philosophy of induction? (shrink)

According to Kripke’s thesis of the necessity of origin, if an object has an origin, it necessarily has that origin. Kripke’s thesis has special cases that we may refer to as “origin theses” when applied to certain types of objects, such as humans and tables. While origin theses have intuitive plausibility, why they are true remains unclear. This paper addresses a prominent line of defense for origin theses. In a celebrated note in Naming and Necessity, Kripke briefly presented an incomplete (...) argument. Advocates of this line of defense attempt to establish origin theses by proposing additional principles with which to complete Kripke’s argument. I call these defenses “Kripkean defenses.” The usual debate in the literature regarding Kripkean defenses has focused on the justifiability of the proposed principles. In this paper, I highlight a neglected issue that arises for Kripkean defenders, even if the debate is assumed to be settled in their favor. I argue that, even if Kripke’s argument is sound, it falls short of establishing origin theses, leaving an inferential gap. How to close the gap is a new problem for Kripkean defenders. My goal in the paper is to offer a solution that I believe is their best hope. If I am right, Kripkean defenders should commit themselves to the Aristotelian view that individuals such as human beings and tables are, in a robust Aristotelian sense, substances with irreducible powers that emerge from the powers of their causal origin. (shrink)

In his recent John Locke Lectures, Robert Brandom defends a view of pragmatism as an extension of the classical project of semantic analysis powerful enough as to incorporate not only relations among meanings, but also, and more fundamentally, relations among meaning and use. The paper explores one of the core aspects of this project – the relation between modal, normative, and empirical vocabularies. Brandom’ focus on a general semantics for non-logical vocabularies intends to meet and answer the empiricist concerns about (...) the intelligibility of modal concepts, which are themselves couched in a modal metavocabulary. Brandom’s purpose is to show that, in using ordinary empirical vocabulary, «in order to be able to talk at all, to make claims and inferences, one must already know how to do everything necessary in principle to deploy modal and normative vocabulary». This is the so-called «Kant-Sellars thesis». In the first part, I present the general framework of analytic pragmatism, the rationale for that project, and its normative foundation. Although the project is in continuity with the goal, pursued in Making It Explicit, of explaining inferential semantics in terms of a normative pragmatics, more structure is added, which clarifies the foundation of the overall enterprise. In the second part, I focus on some objections to the complementary structure of normative and modal vocabularies, and defend a different interpretation of its foundational structure. The goal is to show the modal vocabulary underlies the conceivability and the very inferential practices in which normative vocabulary is involved. (shrink)

Toxic speech inflicts individual and group harm, damaging the social fabric upon which we all depend. To understand and combat the harms of toxic speech, philosophers can learn from epidemiology, while epidemiologists can benefit from lessons of philosophy of language. In medicine and public health, research into remedies for toxins pushes in two directions: individual protections (personal actions, avoidances, preventive or reparative tonics) and collective action (specific policies or widespread “inoculations” through which we seek herd immunity). This paper is the (...) beginning of a project of identifying potential inoculations and antidotes to toxic speech. The essay brings a social practice theory of language, with special reliance on language‐games and inferential roles, into conversation with concepts from the study of biologic toxins. Some speech harms are acute while others are chronic and insidious; they have different methods of delivery, come in variable doses, and not everyone is equally susceptible to the power to harm. I argue that of the many kinds of challenges we might issue against toxic speech, challenging its expressive commitments has the greatest potential to stop the damage. The essay explores the different sorts of protections that inoculations and antidotes might offer against discursive toxins and sketches how to imagine these in the practices that govern our speech. The paper does not make policy recommendations, but an epidemiology of discursive toxicity reveals several kinds of “more speech” that might fight against “bad speech.”. (shrink)

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book offers support for unconscious inference from a slightly different angle, in as much as they defend a proposal on the nature of inference on which consciousness plays no essential role. It examines appeals to unconscious inference in cognitive science. The book explains about the explanatory power of the appeal to unconscious inference – especially unconscious Bayesian inference – in accounts of (...) cognition. It focuses on pragmatic aspects of language comprehension. Several influential accounts of such comprehension agree in viewing it as an inferential achievement: this goes both for Grice’s account and that in relevance theory. The book deals with the traditional thought that inference – at least deductive inference – is structural or formal, and that it, as such, abstracts away from or generalizes across content. (shrink)

The aim of this paper is to characterize the various structuralist reduction concepts as structure-preserving maps in a succinct and unifying way. To begin with, some important intuitive adequacy conditions are discussed that a good (structuralist) reduction concept should satisfy. Having reconstructed these intuitive conditions in the structuralist framework, it turns out that they divide into two mutually incompatible sets of requirements. Accordingly there exist (at least) two essentially different types of structuralist reduction concepts: the first type stresses the existence (...) of a deductive or inferential link between the reducing and the reduced theory; the second type emphasizes the greater explanatory power the reducing theory should have in comparison with the reduced theory. The problem of the incompatibility of equally plausible reduction concepts is treated in the last section and a proposal is made for its solution consisting in the definition of a multiple synthetizing reduction relation. (shrink)

This chapter examines the role played by derogatory terms (e.g., ‘inyenzi’ or cockroach, ‘inzoka’ or snake) in laying the social groundwork for the genocide of the Tutsi in Rwanda in 1994. The genocide was preceded by an increase in the use of anti-Tutsi derogatory terms among the Hutu. As these linguistic practices evolved, the terms became more openly and directly aimed at Tutsi. Then, during the 100 days of the genocide, derogatory terms and coded euphemisms were used to direct killers (...) to their victims. Understanding these speech acts helps to illuminate the important ways that power is enacted through discourse, how speech acts can prepare the way for physical and material acts, and how speech generates permissions for actions hitherto uncountenanced. Studying the role of speech acts and linguistic practices in laying the groundwork of the genocide illuminates how patterns of speech acts become linguistic practices that constitute permissibility conditions for non-linguistic behaviors. Further, the analysis presented here helps to make sense of the view that a steady, deep, and widespread derogation of a group can be part and parcel of genocide, not only an antecedent to it. (shrink)