One of the most difficult problems facing anyone who would discuss Professor Carl Hempel's thesis about explanation is the following: which of the many objections that have been made are actually relevant to the thesis ? Professor Hempel has claimed that several of these objections are not relevant at all ([1], pp. 412-414). In order to evaluate such replies, let me first state what I take to be the three claims which constitute Professor Hempel's thesis.

His first claim is that all adequate scientific explanations possess a certain property:

It is commonly thought that the dispositional view of purposiveness is itself incompatible with the programmatic claims of neurophysiologists. In this paper, various versions of four arguments for this incompatibility are examined, and rejected as unsound. Central to the argument is a rough sketch of a “mechanistic” position which seems clearly compatible with a dispositional view of purposiveness.

Among advocates and critics of the “extended evolutionary synthesis” (EES), “reciprocal causation” refers to the view that adaptive evolution is a bidirectional phenomenon, whereby organisms and environments impinge on each other through processes of niche construction and natural selection. I argue that reciprocal causation is incompatible with the view that natural selection is a metaphysically emergent causal process. The emergent character of selection places reciprocal causation on the horns of dilemma, and neither horn can rescue it. I conclude that proponents of the EES must abandon the claim that the process of natural selection features in cycles of reciprocal causation.

It has been suggested that particle physics has reached the “dawn of the post-naturalness era.” I explain the current shift in particle physicists’ attitude toward naturalness. I argue that the naturalness principle was perceived to be supported by theories it has inspired. The potential coherence between major beyond the standard model (BSM) proposals and the naturalness principle led to an increasing degree of credibility of the principle among particle physicists. The absence of new physics at the Large Hadron Collider (LHC) has undermined the potential coherence and has led to the principle’s loss of significance.

This paper introduces the Cummins Functions Approach to neural representations (CFA), which aims to capture the notion of representation that is relevant to contemporary neuroscientific practice. CFA shares the common view that “to be a representation of X” amounts to “having the function of tracking X,” but maintains that the relevant notion of function is defined by Robert Cummins’s account. Thus, CFA offers a notion of neural representation that is dependent on explanatory context. I argue that CFA can account for the normativity of neural representations, and defend its dependence on explanations.

In a recent note, Horwich (1978) challenges the foundations of Hempel's classic paradox of confirmation by a clever example purporting to show that under Nicod's Criterion, data can be made to confirm a hypothesis with which they are logically incompatible. Specifically, Horwich observes that 'Pb' (i.e., 'object b has property P') is formally equivalent to '(x)(∼Px · ∼Pb ⊃ x ≠ b)'. The latter has form '(x)(ψx ⊃ ϕx)' with '∼P___ · ∼Pb' for 'Ψ' and '___ ≠ b' for 'ϕ', while the observation that distinct objects a and b both lack P, i.e. that —Pa · ∼Pb · a ≠ b, can be expressed as 'Ψa · ϕa' for these same instantiations of the predicate markers. Accordingly, if an uncertain generality '(x)(Ψx ⊃ Ψx)' were always to be confirmed by an observation of form 'Ψa · ϕa', as Nicod's Criterion has long been presumed to say, then we could confirm that b has P by observing that b and some other object both lack P—a flagrant absurdity.

D'Arcy Thompson looked upon himself as a follower of Aristotle in biology, and was an erudite student and translator of biological writings of the Stagyrite. A number of Aristotle's chief terms are to be found in Thompson's masterpiece, On Growth and Form, although these terms—such as ‘cause,’ ‘form,’ ‘movement,’ and the like—undergo some change, generally a contraction, of meaning. But as a tireless investigator of living bodies of all sorts, Thompson developed his own methods for manipulating his concepts, and it is my hope to indicate briefly but critically what the methods are. In so doing, it will be profitable to make comparisons with certain other biologists of past and present, to point up the issues more sharply.

Merging of opinions results underwrite Bayesian rejoinders to complaints about the subjective nature of personal probability. Such results establish that sufficiently similar priors achieve consensus in the long run when fed the same increasing stream of evidence. Here, we establish a merging result for sets of probability measures updated by Jeffrey conditioning. This generalizes a number of different merging results in the literature. We also show that such sets converge to a shared, maximally informed opinion. Finally, we demonstrate the philosophical significance of our study by detailing applications to the topics of dynamic coherence, imprecise probabilities, and opinion pooling.

There seem to be some very good reasons for a philosopher of science to be a deductivist about scientific reasoning. Deductivism is apparently connected with a demand for clarity and definiteness in the reconstruction of scientists' reasonings. And some philosophers even think that deductivism is the way around the problem of induction. But the deductivist image is challenged by cases of actual scientific reasoning, in which hard-to-state and thus discursively ill-defined elements of thought nonetheless significantly condition what practitioners accept as cogent argument. And arguably, these problem cases abound. For example, even geometry—for most of its history—was such a problem case, despite its exactness and rigor. It took a tremendous effort on the part of Hilbert and others, to make geometry fit the deductivist image. Looking to the empirical sciences, the problems seem worse. Even the most exact and rigorous of empirical sciences—mechanics—is still the kind of problem case which geometry once was. In order for the deductivist image to fit mechanics, Hilbert's sixth problem (for mechanics) would need to be solved. This is a difficult, and perhaps ultimately impossible task, in which the success so far achieved is very limited. I shall explore some consequences of this for realism as well as for deductivism. Through discussing links between non-monotonicity, skills, meaning, globality in cognition, models, scientific understanding, and the ideal of rational unification, I argue that deductivists can defend their image of scientific reasoning only by trivializing it, and that for the adequate illumination of science, insights from anti-deductivism are needed as much as those which come from deductivism.

Thomas Polger and Lawrence Shapiro claim that unlike human-made artifacts cases of multiple realization in naturally occurring systems are uncommon. Drawing on cases from systems biology, I argue that multiple realization in naturally occurring systems is not as uncommon as Polger and Shapiro initially thought. The relevant cases, which I draw from systems biology, involve generalizable design principles called network motifs, which recur in different organisms and species and perform specific functions. I show that network motifs with entirely different underlying causal structures can perform the same function of interest. The article also considers the scope problem of multiple realization.

The history of Western culture exhibits a profound cleavage of opinion on the nature of what its members take to be reality. On the one hand, there are those for whom certain aspects, at least, of the “real” exist in the human mind only. Others assign as the sole basis of reality the world of non-mental objects. This difference of temperament is so pervasive that it forms a perennial theme, not only for philosophers, but also for scientists, poets, and other students of the vast panorama of the world and its people.

The following statement from James’ 1884 essay in Mind (12) is repeated in his later work (10, pp. 100–101) and appears often in secondary sources as a summary of his celebrated theory of the emotions:

Although scientific images have begun to receive significant attention from philosophers, one type of image has thus far been ignored: moving images. As techniques such as live cell imaging and videomicroscopy are becoming increasingly important in many areas of biology, however, this oversight needs to be corrected. Biologists often claim that there are relevant differences between video and static images. Most interesting is the idea that video images allow us to see causal relationships. By identifying the conditions that would be required for this to be true and showing that they are not satisfied at the micro level, I will show that videomicroscopy does not provide us with special access to causal information.

It is my pleasant task to open a series of discussions on the sciences which will continue here in Cooper Union for the rest of the season. A few words are necessary, therefore, to indicate the design of the pattern of the lecture series as a whole, as well as the specific place and quality of my own lecture.

Generalized Darwinism models cultural development as an evolutionary process, where traits evolve through variation, selection, and inheritance. Inheritance describes either a discrete unit’s transmission or a mixing of traits (i.e., blending inheritance). In this article, we compare classical models of cultural evolution and generalized population dynamics with respect to blending inheritance. We identify problems of these models and introduce our model, which combines relevant features of both. Blending is implemented as success-based social learning, which can be shown to be an optimal strategy.

Philosophical discussions of information and specificity in biology are now commonplace, but no consensus exists about whether the privileging of genetic causation in investigation and explanation is justified. However, little effort has been expended on understanding practices when scientists experimentally measure information or causal specificity. An example of this type of practice—measuring positional information in gene expression during pattern formation in embryogenesis—shows that biologists are unconcerned with comparing the amount of information in genes with that of other factors. Instead, they focus on whether the measured causal specificity explains the phenomenon under scrutiny.

“The age-long endeavour to find an intellectual basis for ethics is an enterprise of such importance, and of such difficulty, that any explorer of that country must always be glad to hear the voices of his fellow-travellers. ‘This,’ Wittgenstein once said to me, ‘is a terrible business—just terrible! You can at best stammer when you talk of it.’”

With these words Waddington introduces his symposium Science and Ethics, a “communal, perhaps even co-operative stammering,” as he calls it. Also the present contribution to the “terrible business” cannot be more than a stammering; The business is so terrible today not only because of its inherent difficulties, but because of the tremendous odds which are at stake. When the Renaissance philosophers built the science of material nature they were fired by an enthusiasm of cosmic exploration. Today we are frozen in awe of a cosmic explosion. When Galileo pioneered his new science he knew that he was in the possession of the truth and that his opponents, steeped in error and superstition, would have to give way—eppur si muove! Today, building the science of ethics, we are neither equally sure nor equally confident. Our science is not yet formulated. Our opponents, though not right, may yet conquer before we have had time to develop the new science. We are not sure whether what was true for physics three hundred years ago is true for ethics today.

Carl G. Hempel's doctrine of essential epistemic relativization of inductive-statistical explanation seems to entail the unintelligibility of the notion of objective homogeneity of reference classes. This discussion note explores the question of whether, as a consequence, essential epistemic relativization also entails the unintelligibility of the doctrine of indeterminism.