This paper presents a new analysis of C.G. Hempel’s conditions of adequacy for any relation of confirmation [Hempel C. G. (1945). Aspects of scientific explanation and other essays in the philosophy of science. New York: The Free Press, pp. 3–51.], differing from the one Carnap gave in §87 of his [1962. Logical foundations of probability (2nd ed.). Chicago: University of Chicago Press.]. Hempel, it is argued, felt the need for two concepts of confirmation: one aiming at true hypotheses and another (...) aiming at informative hypotheses. However, he also realized that these two concepts are conflicting, and he gave up the concept of confirmation aiming at informative hypotheses. I then show that one can have Hempel’s cake and eat it too. There is a logic that takes into account both of these two conflicting aspects. According to this logic, a sentence H is an acceptable hypothesis for evidence E if and only if H is both sufficiently plausible given E and sufficiently informative about E. Finally, the logic sheds new light on Carnap’s analysis. (shrink)

The problem addressed in this paper is “the main epistemic problem concerning science”, viz. “the explication of how we compare and evaluate theories [...] in the light of the available evidence” (van Fraassen, BC, 1983, Theory comparison and relevant Evidence. In J. Earman (Ed.), Testing scientific theories (pp. 27–42). Minneapolis: University of Minnesota Press). Sections 1– 3 contain the general plausibility-informativeness theory of theory assessment. In a nutshell, the message is (1) that there are two values a theory should exhibit: (...) truth and informativeness—measured respectively by a truth indicator and a strength indicator; (2) that these two values are conflicting in the sense that the former is a decreasing and the latter an increasing function of the logical strength of the theory to be assessed; and (3) that in assessing a given theory by the available data one should weigh between these two conflicting aspects in such a way that any surplus in informativeness succeeds, if the shortfall in plausibility is small enough. Particular accounts of this general theory arise by inserting particular strength indicators and truth indicators. In Section 4 the theory is spelt out for the Bayesian paradigm of subjective probabilities. It is then compared to incremental Bayesian confirmation theory. Section 4 closes by asking whether it is likely to be lovely. Section 5 discusses a few problems of confirmation theory in the light of the present approach. In particular, it is briefly indicated how the present account gives rise to a new analysis of Hempel’s conditions of adequacy for any relation of confirmation (Hempel, CG, 1945, Studies in the logic of comfirmation. Mind, 54, 1–26, 97–121.), differing from the one Carnap gave in § 87 of his Logical foundations of probability (1962, Chicago: University of Chicago Press). Section 6 adresses the question of justification any theory of theory assessment has to face: why should one stick to theories given high assessment values rather than to any other theories? The answer given by the Bayesian version of the account presented in section 4 is that one should accept theories given high assessment values, because, in the medium run, theory assessment almost surely takes one to the most informative among all true theories when presented separating data. The concluding section 7 continues the comparison between the present account and incremental Bayesian confirmation theory. (shrink)

We reconsider the Nagelian theory of reduction and argue that, contrary to a widely held view, it is the right analysis of intertheoretic reduction. The alleged difficulties of the theory either vanish upon closer inspection or turn out to be substantive philosophical questions rather than knock-down arguments.

Bayesian Coherence Theory of Justification or, for short, Bayesian Coherentism, is characterized by two theses, viz. (i) that our degree of confidence in the content of a set of propositions is positively affected by the coherence of the set, and (ii) that coherence can be characterized in probabilistic terms. There has been a longstanding question of how to construct a measure of coherence. We will show that Bayesian Coherentism cannot rest on a single measure of coherence, but requires a vector (...) whose components exhaustively characterize the coherence properties of the set. Our degree of confidence in the content of the information set is a function of the reliability of the sources and the components of the coherence vector. The components of this coherence vector are weakly but not strongly separable, which blocks the construction of a single coherence measure. (shrink)

Exploring recent controversies over the role of ethics in economics, The Boundaries of Technique encourages scholars and students to discover and debate the ways in which economics is insulated from ethics, and the ways in which it is dependent upon it. Ultimately, by bringing readers to a deeper awareness of the intrinsic involvement of the individual and the responsibility of moral choice, Yuengert makes an invaluable contriubtion to the study and practice of economics.

Scientists can choose different claims as interpretations of the results of their research. Scientific rhetoric is understood as the attempt to make those claims most beneficial for the scientists' interests. A rational choice, game-theoretic model is developed to analyze how this choice can be made and to assess it from a normative point of view. The main conclusion is that `social' interests (pursuit of recognition) may conflict with `cognitive' ones when no constraints are put on the choices of the authors (...) of scientific papers, as in an `ideal free speech situation'. Scientific institutions may help to solve this conflict. Lastly, some empirical predictions are offered that can inspire future social research of the refereeing process. (shrink)

I. A. Kieseppä's criticism of the methodological use of the theory of verisimilitude, and D. B. Resnik's arguments against the explanation of scientific method by appeal to scientific aims are critically considered. Since the notion of verisimilitude was introduced as an attempt to show that science can be seen as a rational enterprise in the pursuit of truth, defenders of the verisimilitude programme need to show that scientific norms can be interpreted as rules that try to increase the degree of (...) truthlikeness of scientific theories. This possibility is explored for several approaches to the problem of verisimilitude. (shrink)

This article analyzes the epistemic value of understanding and offers an account of the role of understanding in science. First, I discuss the objectivist view of the relation between explanation and understanding, defended by Carl Hempel and J. D. Trout. I challenge this view by arguing that pragmatic aspects of explanation are crucial for achieving the epistemic aims of science. Subsequently, I present an analysis of these pragmatic aspects in terms of ‘intelligibility’ and a contextual account of scientific understanding based (...) on this notion. †To contact the author, please write to: Faculty of Philosophy, VU University Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands; e‐mail: [email protected]. (shrink)

The naive structuralist definition of truthlikeness is an idealization in the sense that it assumes that all mistaken models of a theory are equally bad. The natural concretization is a refined definition based on an underlying notion of structurelikeness.In Section 1 the naive definition of truthlikeness of theories is presented, using a new conceptual justification, in terms of instantial and explanatory mistakes.

This essay contains a partial exploration of some key concepts associated with the epistemology of realist philosophies of science. It shows that neither reference nor approximate truth will do the explanatory jobs that realists expect of them. Equally, several widely-held realist theses about the nature of inter-theoretic relations and scientific progress are scrutinized and found wanting. Finally, it is argued that the history of science, far from confirming scientific realism, decisively confutes several extant versions of avowedly 'naturalistic' forms of scientific (...) realism. (shrink)

1. The problem. The concept of confirmation of an hypothesis by empirical evidence is of fundamental importance in the methodology of empirical science. For, first of all, a sentence cannot even be considered as expressing an empirical hypothesis at all unless it is theoretically capable of confirmation or disconfirmation, i.e. unless the kind of evidence can be characterized whose occurrence would confirm, or disconfirm, the sentence in question. And secondly, the acceptance or rejection of a sentence which does represent an (...) empirical hypothesis is determined, in scientific procedure, by the degree to which it is confirmed by relevant evidence. (shrink)

The old evidence problem affects any probabilistic confirmation measure based on comparing pr(H/E) and pr(H). The article argues for the following points: (1) measures based on likelihood ratios also suffer old evidence difficulties; (2) the less-discussed synchronic old evidence problem is, in an important sense, the most acute; (3) prominent attempts to solve or dissolve the synchronic problem fail; (4) a little-discussed variant of the standard measure avoids the problem, in an appealing way; and (5) this measure nevertheless reveals a (...) different problem for probabilistic confirmation measures, a problem that is unlikely to lend itself to formal solution. (shrink)

Some peculiarities of the evaluation of theories within scientific research programmes and of the assessing of rival SRPs are described assuming that scientists try to maximise an ‘epistemic utility function’ under economic and institutional constraints. Special attention is given to Lakatos' concepts of ‘empirical progress’ and ‘theoretical progress’. A notion of ‘empirical verisimilitude’ is defended as an appropriate utility function. The neologism ‘methodonomics’ is applied to this kind of studies.

Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation. In this article, we present a Bayesian analysis of how GNS impacts on confirmation. We formalize the relation between the reducing and the reduced theory before and after the reduction using Bayesian networks, and thereby show that, post-reduction, the two theories are confirmatory of each other. We (...) then ask when a purported reduction should be accepted on epistemic grounds. To do so, we compare the prior and posterior probabilities of the conjunction of both theories before and after the reduction and ask how well each is confirmed by the available evidence. (shrink)

An epistemic notion of verisimilitude (as the 'degree in which a theory seems closer to the full truth to a scientific community') is defined in several ways. Application to the structuralist description of theories is carried out by introducing a notion of 'empirical regularity' in structuralist terms. It is argued that these definitions of verisimilitude can be used to give formal reconstructions of scientific methodologies such as falsificationism, conventionalism and normal science.

Lateral gene transfer, the exchange of genetic information between lineages, not only makes construction of a universal Tree of Life difficult to achieve, but calls into question the utility and meaning of any result. Here I review the science of prokaryotic LGT, the philosophy of the TOL as it figured in Darwin’s formulation of the Theory of Evolution, and the politics of the current debate within the discipline over how threats to the TOL should be represented outside it. We could (...) encourage a more realistic and supportive public understanding of evolution by admitting that what we believe in is not a unified meta-theory but a versatile and well-stocked explanatory toolkit. (shrink)

Being scientific research a process of social interaction, this process can be studied from a game-theoretic perspective. Some conceptual and formal instruments that can help to understand scientific research as a game are introduced, and it is argued that game theoretic epistemology provides a middle ground for 'rationalist' and 'constructivist' theories of scientific knowledge. In the first part , a description of the essential elements of game of science is made, using an inferentialist conception of rationality. In the second part (...) , some ideas for the reconstruction of case studies are introduced, and applied to one example: Latour's analysis of Joliot's attempt to build an atomic bomb. Lastly, in the third part , a formal analysis of the constitution of scientific consensus is offered. (shrink)

The incredible achievements of modern scientific theories lead most of us to embrace scientific realism: the view that our best theories offer us at least roughly accurate descriptions of otherwise inaccessible parts of the world like genes, atoms, and the big bang. In Exceeding Our Grasp, Stanford argues that careful attention to the history of scientific investigation invites a challenge to this view that is not well represented in contemporary debates about the nature of the scientific enterprise. The historical record (...) of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself. Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true. (shrink)

Methodological norms are seen as rules defining a competitive game, and it is argued that rational recognition-seeking scientists can reach a collective agreement about which specific norms serve better their individual interests, especially if the choice is made `under a veil of ignorance', i.e. , before knowing what theory will be proposed by each scientist. Norms for theory assessment are distinguished from norms for theory choice (or inference rules), and it is argued that pursuit of recognition only affects this second (...) type of rule. An inference rule similar to `eliminative induction' is defended on the basis of such a possible agreement. According to this contractarian approach, both the explanation and the justification of scientific norms only need to refer to the preferences of individual scientists, without assuming the existence of `collective' points of view. (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)