It is the aim of this paper to examine certain aspects of a point of view which has attracted much attention in physical methodology. This is the standpoint known as operationalism. We wish to discuss its significance in the construction and interpretation of physical theories.

The essential meaning of operationalism in physics is that physical concepts should be defined in terms of actual physical operations. On this view there is no meaning to a concept unless it represents an operation which can be performed in the laboratory. Thus the term “pressure of a gas” signifies nothing until an operation is described which constitutes the measurement of pressure. When one thinks of pressure one must think. of some actual apparatus, such as, for example, some glass and rubber tubing and some mercury and certain operations performed using these until finally one gets a pointer reading which one calls the pressure of the gas. The same stand is taken with respect to length, time, velocity, acceleration, temperature, etc.

This paper is an attempt at a vindication of induction. The point of departure is that induction requires a justification and that the only kind of justification possible is a vindication. However traditional vindications of induction have rested on unjustified assumptions about the aim of induction. This vindication takes the end pursued in induction simply to be correct prediction. It is argued that induction is the only reasonable way of pursuing this end because induction is the only objective method of predicting. While objectivity is not a necessary condition for successful predicting, it is a sufficient condition for the possession of a property that is, in turn, a necessary condition for correct predicting; and further there could be no reason to expect any non-objective method to possess this necessary condition for success.

Induction is the only objective method of predicting for it alone uses facts which must be identified by any predicting method based on rules; and it alone uses these facts according to a relationship that must hold between facts and any meaningful empirical statement. Any alternative to induction must assume that the factual regularities that have been detected will alter in the future and the way they are expected to alter must be arbitrary. It is further claimed that this vindication is proof against the criticisms that have been advanced against practicalist justifications of induction.

The new field of meta-research investigates industry bias, publication bias, contradictions between studies, and other trends in medical research. I argue that its findings should be used as meta-evidence for evaluating therapies. ‘Meta-evidence’ is evidence about the support that direct ‘first-order evidence’ provides the hypothesis. I consider three objections to my proposal: the irrelevance objection, the screening-off objection, and the underdetermination objection. I argue that meta-research evidence works by rationally revising our confidence in first-order evidence and, consequently, in the hypothesis—typically, downward.

Philosophers of science are increasingly interested in engaging with scientific communities, policy makers, and members of the public; however, the nature of this engagement has not been systematically examined. Instead of delineating a specific kind of engaged philosophy of science, as previous accounts have done, this article draws on literature from outside the discipline to develop a framework for analyzing different forms of broadly engaged philosophy of science according to two key dimensions: social interaction and epistemic integration. Clarifying the many forms of engagement available to philosophers of science can advance future scholarship on engagement and promote more strategic engagement efforts.

In this article I articulate the Theory of Affective Pragmatics, which combines insights from the Basic Emotion View and the Behavioral Ecology View of emotional expressions. My core thesis is that emotional expressions are ways of manifesting one’s emotions but also of representing states of affairs, directing other people’s behaviors, and committing to future courses of actions. Since these are some of the main things we can do with language, my article’s take home message is that, from a communicative point of view, much of what we can do with language we can also do with nonverbal emotional expressions.

There is a vast literature within philosophy of mind that focuses on artificial intelligence but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and targets are picked out, how modeling inferences are justified, and the metaphysical status of models.

Two articles on the reduction of chemistry are examined. The first, by McLaughlin (1992), claims that chemistry is reduced to physics and that there is no evidence for emergence or for downward causation between the chemical and the physical level. In a more recent article, Le Poidevin (2005) maintains that his combinatorial approach provides grounding for the ontological reduction of chemistry, which also circumvents some limitations in the physicalist program.

Alexander Rosenberg (1983) has argued, contrary to his previous work in the philosophy of economics, that economics is not science, and it is merely mathematics. The following paper argues that Rosenberg fails to demonstrate either of these two claims. The questions of the predictive weakness of modern economics and the cognitive standing of abstract economic theory are discussed in detail.

John Worrall recently provided an account of epistemic structural realism, which explains the success of science by arguing for the correct mathematical structure of our theories. He accounts for the historical failures of science by pointing to bloated ontological interpretations of theoretical terms. In this paper I argue that Worrall's account suffers from five serious problems. I also show that Pierre Cruse and David Papineau have developed a rival structural realism that solves all of the problems faced by Worrall. This Ramsey sentence realism is a significant advance in the debate, but still ultimately fails for its incomplete account of reference

According to the Fine-Tuning Argument (FTA), the existence of life in our universe confirms the Multiverse Hypothesis (HM). A standard objection to FTA is that it violates the Requirement of Total Evidence (RTE). I argue that RTE should be rejected in favor of the Predesignation Requirement, according to which, in assessing the outcome of a probabilistic process, we should only use evidence characterizable in a manner available before observing the outcome. This produces the right verdicts in some simple cases in which RTE leads us astray, and, when applied to FTA, it shows that our evidence does confirm HM.

Peter Lipton has attempted to flesh out a model of Inference to the Best Explanation (IBE) by clarifying explanation in terms of a causal model. But Lipton's account of explanation makes an adequate explanation depend on a principle which is virtually identical to Mill's Method of Difference. This has the result of collapsing IBE on Lipton's account of it into causal inference as conceived by the Causal-Inference model of induction. According to this model, many of our inductions are inferences from effects to their probable causes, and Mill's Methods are canons to guide such inferences. Thus, Lipton's account of IBE fails to represent an advance over the already familiar Causal-Inference Model of induction.

I argue against the conception of scientific models advocated by the proponents of the Semantic View of scientific theories. Part of the paper is devoted to clarifying the important features of the scientific modeling view that the Semantic conception entails. The liquid drop model of nuclear structure is analyzed in conjunction with the particular auxiliary hypothesis that is the guiding force behind its construction and it is argued that it does not meet the necessary features to render it a model of the theory, as the Semantic View demands. Given that this model is indicative of how quantum mechanics is applied in the domain of nuclear physics, I claim that the Semantic View does not adequately account for scientific models.

The view is advocated that to preserve a deductivist account of science against recent criticism, it is necessary to incorporate experimental error, or imprecision, in the deductive structure. The sources of imprecision in empirical variables are analyzed, and the notion of conceptual imprecision introduced and illustrated. This is then used to clarify the notion of the acceptable range of a functional law. It is further shown that imprecision may be ascribed to parameters in laws and theories without rendering the deductive structure untestable. It is claimed that this analysis explicates the relation between laws and theories in a way that invalidates certain arguments against its deductive nature.

Paul Teller's (1995) new book, “An Interpretive Introduction to Quantum Field Theory”, is a pioneering work. To the best of our knowledge it is the first book by a philosopher devoted not only to explaining what quantum field theory (QFT) is, but to clarifying the conceptual issues and puzzles to which the theory gives rise (though Auyung 1995 treats some different issues in QFT). As such it is an important book, which we hope will greatly stimulate work in the area as other philosophers and physicists react to it.

During my recent work on machine translation (3), I have come across many problems of a linguistic nature that should be of general methodological interest. Some of these problems have never been treated extensively before. Others that have been discussed previously appear now in a different and rather interesting light.

There is still a great deal of debate over what counts as a constraint and about how to assess experimentally the relative importance of constraints and selection in evolutionary history. I will argue that the notion of a constraint on variation, and thus the selection-constraint distinction, depends on two specifications: (1) what counts as a variant—constraints limit or bias the production of what? and (2) range of assessment—over what range of times or conditions is the variation assessed? Specifications 1 and 2 help us to understand empirical work on the relative importance of constraint and selection in evolution.

The purpose of this paper is to make clear (1) that the widely recognized formulations of the principle of induction do not express the most fundamental rule of induction; (2) that the current view concerning the probability of induction must be revised in terms of a frequency theory of probability; (3) that on this basis the problem of induction in its traditional form is a pseudo-problem; and (4) that the principle of induction must be interpreted as a pragmatic or operational maxim.

I outline Gould's conception of evolutionary theory and his ways of contrasting it with contemporary Darwinism; a contemporary Darwinism that focuses on the natural selection of individual organisms. Gould argues for a hierarchical conception of the living world and of the evolutionary processes that have built that living world: organisms are built from smaller components (genes, cells) and are themselves components of groups, populations, species, lineages. Selection, drift and constraint are important to all of these levels of biological organization, not just that of individual organisms. Moreover, both drift and constraint are more important than orthodoxy supposes. While having some sympathy for both of these lines of argument, I argue that they are more problematic than Gould supposes, and that he understates the power and the heterogeneity of orthodox conceptions of life's evolution.

In his recent address to the Aristotelian Society, Aurel Kolnai suggests that games exhibit what he calls a “genuine paradoxy.” I do not believe that he has shown this to be the case, even on the most permissive interpretation of what it means to be a paradox. Kolnai has, however, called attention to an aspect of games which invites further investigation, and I should like to advance the following considerations not so much as a criticism of Kolnai as an attempt to take the investigation along a path which Kolnai has indicated, but which he has not himself, in my opinion, followed. It is not that Kolnai does not say many interesting, indeed penetrating, things about games, for he does. That Kolnai's inquiry is an important contribution to the philosophy of games is not in question. What is questionable is whether paradox has very much to do with that contribution.