Combining classical logic, paraconsistency and relevance

We present a logic with has both a simple semantics and a cut-free Gentzen-type system on one hand, and which combines relevance logics, da Costa's paraconsistent logics, and classical logic on the other. We further show that the logic has many other nice properties, and that its language is ideal from the semantic point of view.     

The Undecidability of Propositional Adaptive Logic

We investigate and classify the notion of final derivability of two basic inconsistency-adaptive logics. Specifically, the maximal complexity of the set of final consequences of decidable sets of premises formulated in the language of propositional logic is described. Our results show that taking the consequences of a decidable propositional theory is a complicated operation. The set of final consequences according to either the Reliability Calculus or the Minimal Abnormality Calculus of a decidable propositional premise set is in general undecidable, and can be -complete. These classifications are exact. For first order theories even finite sets of premises can generate such consequence sets in either calculus.     

Probability, logic and the cognitive foundations of rational belief

Since Pascal introduced the idea of mathematical probability in the 17th century discussions of uncertainty and “rational” belief have been dogged by philosophical and technical disputes. Furthermore, the last quarter century has seen an explosion of new questions and ideas, stimulated by developments in the computer and cognitive sciences. Competing ideas about probability are often driven by different intuitions about the nature of belief that arise from the needs of different domains (e.g., economics, management theory, engineering, medicine, the life sciences etc). Taking medicine as our focus we develop three lines of argument (historical, practical and cognitive) that suggest that traditional views of probability cannot accommodate all the competing demands and diverse constraints that arise in complex real-world domains. A model of uncertain reasoning based on a form of logical argumentation appears to unify many diverse ideas. The model has precursors in informal discussions of argumentation due to Toulmin, and the notion of logical probability advocated by Keynes, but recent developments in artificial intelligence and cognitive science suggest ways of resolving epistemological and technical issues that they could not address.     

Philosophy of science and the foundations of psychotherapy

The field of psychotherapy rests on a foundation of basic propositions, fundamental starting points or cornerstones, and ideas that are generally taken for granted as fundamental givens or truths. A case is presented that there are ways in which foundational beliefs may be kept essentially immune from careful explication, study, examination, analysis, and challenge, and therefore from constructive improvement and change. Borrowed largely from the neighboring field of philosophy of science, 5 solutions are presented to assist in explicating, challenging, improving, and changing foundational beliefs. The subsequent 2 articles (E. Erwin, 2000; J. F. Rychlak, 2000) illustrate how these philosophy of science methods may be applied to 2 foundational beliefs in the field of psychotherapy.     

The triad of science foundations, instructional technology, and organizational structure

Over the centuries and across all societies educational achievement does not improve. The attempt to improve the instructional process has concentrated on instructional technology. But these attempts have overlooked the importance of two other factors: the science that should underlie the instructional technologies and the organization that must operate those technologies. A considerable step forward in handling the problems of instructional effectiveness has been the derivation of instructional technologies based on Skinnerian science. But the instructional technologies based on Skinner's analysis of behavior are promoted as if they were to operate in an organizational vacuum. The division of labor, and its necessary coordination and control, is taken for granted. But in any large scale enterprise, the organization of the division of labor must fit the technology through which that enterprise achieves its mission. Educational technology must tie directly to a pertinent science and to a proper organizational structure. To teach effectively requires an overhaul along three lines: 1) a relevant science that reflects and encapsulates an accurate understanding of behavior; 2) a contingency-based technology of instruction that directly derives its practices upon proper scientific principles; and 3) a suitable organization based on teaching teams that operate the new instructional technology.     

The biological foundations of cognitive science

Cognitive Science originated in reactions against behaviorism that were motivated in significant part by the example of the computer. The computer raised the exciting possibility that mind could be understood almost entirely independently of brain: if the operations of the mind are akin to the execution of a program, then almost all the relevant aspects of mind would be captured by that program, independently of whatever was running it, be it transistors or neurons. This presumed independence of cognitive science from biology has waned considerably in recent decades, but in this paper, I argue that there is at least one crucial aspect of biology that has yet to be appreciated for its relevance to mental and other normative processes—the thermodynamics of living systems. In particular, I argue that the emergence of normativity in general—and normative function and representation in particular—depends on special systems that are far from thermodynamic equilibrium; these form the interface between the factual world of atoms and molecules and the normative world of mind. The nature of that emergence, in turn, imposes strong constraints on how the central nervous system functions, and, therefore, on how cognition is realized.     

Arthur F. Bentley and the foundations of behavioral science

Arthur F. Bentley's early work on the foundations of behavioral science has been neglected by students of the history and philosophy of social science. Bentley believed that the development of behavioral science required extensive reflection on and criticism of the categorial presuppositions of both everyday and scientific knowledge. This paper is concerned with Bentley's criticism of psychological explanation, his theory of observation, and the basic concepts of his behavioral science.     

The fantasy of third-person science: Phenomenology, ontology and evidence

Dennett’s recent defense in this journal of the heterophenomenological method and its supposed advantages over Husserlian phenomenology is premised on his problematic account of the epistemological and ontological status of phenomenological states. By employing Husserl’s philosophy of science to clarify the relationship between phenomenology and evidence and the implications of this relationship for the empirical identification of ‘real’ conscious states, I argue that the naturalistic account of consciousness Dennett hopes for could be authoritative as a science only by virtue of the very phenomenological evidences Dennett’s method consigns to the realm of fiction. Thus heterophenomenology, qua scientific method, is incoherent.

Philosophical foundations of partial belief models

This paper is an attempt to put forward a new kind of partial model for representing belief states. I first introduce some philosophical motivations for working with partial models. Then, I present the standard (total) model proposed by Hintikka, and the partial models studied by Humberstone and Holliday. I then show how to reduce Hintikka’s semantics in order to obtain a partial model which, however, differs from Humberstone’s and Holliday’s. The nature of such differences is assessed, and I provide motivations for using the newly proposed semantics rather than the existing ones. Finally, I review some promising philosophical applications of the ideas developed throughout the discussion.     

An examination of the SEP candidate analogical inference rule within pure inductive logic

Within the framework of (Unary) Pure Inductive Logic we investigate four possible formulations of a probabilistic principle of analogy based on a template considered by Paul Bartha in the Stanford Encyclopedia of Philosophy [1] and give some characterizations of the probability functions which satisfy them. In addition we investigate an alternative interpretation of analogical support, also considered by Bartha, based not on the enhancement of probability but on the creation of possibility.     

Empiricism,judgment, and argument; Toward an informal logic of science

In an attempt to explore the role of argumentation in scientific inquiry, I explore the conception of argument that appears fruitful in the light of the recent trends in the philosophy of science, away from logical empiricism, and toward a greater emphasis on change, disagreement, and history. I begin by contrasting typical instances philosopers theories of both empiricism and apriorism, with typical instances of scientists uses of these two attitudes, suggesting that such practice shows a judiciousness lacking in epistemological theory. Then I examine at some length three important version of scientific judgement, namely Einstein's opportunism, Boltzmann's pluralism, and Huygens's eclecticism. I go on to discuss some recent work in the philosophy of science, exploring connections between the notion of judgment and Feyerabend's anarchism, Harold Brown's view of rationality, and Dudley Shapere's analysis of scientific change. All of this suggests a notion of argument in the sense of informallogic, and I examine some aspects of Galileo's work in its terms.     

The ontological commitments of inconsistent theories

In this paper I present an argument for belief in inconsistent objects. The argument relies on a particular, plausible version of scientific realism, and the fact that often our best scientific theories are inconsistent. It is not clear what to make of this argument. Is it a reductio of the version of scientific realism under consideration? If it is, what are the alternatives? Should we just accept the conclusion? I will argue (rather tentatively and suitably qualified) for a positive answer to the last question: there are times when it is legitimate to believe in inconsistent objects.     

Models and fictions in science

Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.

Coherence versus fragmentation in the development of the concept of force

This article aims to contribute to the literature on conceptual change by engaging in direct theoretical and empirical comparison of contrasting views. We take up the question of whether naïve physical ideas are coherent or fragmented, building specifically on recent work supporting claims of coherence with respect to the concept of force by Ioannides and Vosniadou [Ioannides, C., & Vosniadou, C. (2002). The changing meanings of force. Cognitive Science Quarterly 2, 5-61]. We first engage in a theoretical inquiry on the nature of coherence and fragmentation, concluding that these terms are not well-defined, and proposing a set of issues that may be better specified. The issues have to do with contextuality, which concerns the range of contexts in which a concept (meaning, model, theory) applies, and relational structure, which is how elements of a concept (meaning, model, or theory) relate to one another. We further propose an enhanced theoretical and empirical accountability for what and how much one needs to say in order to have specified a concept. Vague specification of the meaning of a concept can lead to many kinds of difficulties.Empirically, we conducted two studies. A study patterned closely on Ioannides and Vosniadou's work (which we call a quasi-replication) failed to confirm their operationalizations of “coherent.” An extension study, based on a more encompassing specification of the concept of force, showed three kinds of results: (1) Subjects attend to more features than mentioned by Ioannides and Vosniadou, and they changed answers systematically based on these features; (2) We found substantial differences in the way subjects thought about the new contexts we asked about, which undermined claims for homogeneity within even the category of subjects (having one particular meaning associated with “force”) that best survived our quasi-replication; (3) We found much reasoning of subjects about forces that cannot be accounted for by the meanings specified by Ioannides and Vosniadou. All in all, we argue that, with a greater attention to contextuality and with an appropriately broad specification of the meaning of a concept like force, Ioannides and Vosniadou's claims to have demonstrated coherence seem strongly undermined. Students’ ideas are not random and chaotic; but neither are they simply described and strongly systematic.     

The step to rationality: the efficacy of thought experiments in science, ethics, and free will

Examples from Archimedes, Galileo, Newton, Einstein, and others suggest that fundamental laws of physics were—or, at least, could have been—discovered by experiments performed not in the physical world but only in the mind. Although problematic for a strict empiricist, the evolutionary emergence in humans of deeply internalized implicit knowledge of abstract principles of transformation and symmetry may have been crucial for humankind's step to rationality—including the discovery of universal principles of mathematics, physics, ethics, and an account of free will that is compatible with determinism.     

Seeing and believing: perception,belief formation and the divided mind

On many of the idealized models of human cognition and behavior in use by philosophers, agents are represented as having a single corpus of beliefs which (a) is consistent and deductively closed, and (b) guides all of their (rational, deliberate, intentional) actions all the time. In graded-belief frameworks, agents are represented as having a single, coherent distribution of credences, which guides all of their (rational, deliberate, intentional) actions all of the time. It’s clear that actual human beings don’t live up to this idealization. The systems of belief that we in fact have are fragmented. Rather than having a single system of beliefs that guides all of our behavior all of the time, we have a number of distinct, compartmentalized systems of belief, different ones of which drive different aspects of our behavior in different contexts. It’s tempting to think that, while of course people are fragmented, it would be better (from the perspective of rationality) if they weren’t, and the only reason why our fragmentation is excusable is that we have limited cognitive resources, which prevents us from holding too much information before our minds at a time. Give us enough additional processing capacity, and there’d be no justification for any continued fragmentation. I argue that this is not so. There are good reasons to be fragmented rather than unified, independent of the limitations on our available processing power. In particular, there are ways our belief-forming mechanisms—including our perceptual systems—could be constructed that would make it better to be fragmented than to be unified. And there are reasons to think that some of our belief-forming mechanisms really are constructed that way.

Keeping the heart a long way from the brain: The emotional labour of climate scientists

This paper contributes to increased understanding of emotions and climate change through a study of the emotional management strategies employed by a sample of Australian climate scientists. We bring three broad areas of literature into conversation in order to think more productively about climate change and emotion: recent applications of the concept of emotional labour, studies of the role of emotion in science, and feminist perspectives on the performative role of emotions. In response to contextual drivers that include the social norms of science, a strong climate denialist influence and the preservation of self and family, these scientists mobilize a range of behaviours and strategies to manage their emotions around climate change and the future. These include emphasizing dispassion, suppressing painful emotions, using humour and switching off from work. Emotional denial or suppression of the consequences of climate change worked to enable the scientists to persevere in their work. This study suggests that painful emotions (anxiety, fear, loss) around climate change need to be acknowledged and discussed.