We focus on a neglected aspect of scientific theory choice: how the selection of theories affects epistemic values. Building on Kuhn, we provide a general characterization of the feedback-loop dynamic between theories and values in theory choice as analogous to the relationship between organisms and the environment in niche construction. We argue that understanding theory choice as niche construction can explain how certain values acquire more weight and a specific application over time, and how resistance to scientific change can, therefore, arise. We illustrate our picture by looking at the Mendelian–biometrician controversy.

Standard defenses of ontological individualism are challenged by arguments that exploit the dependence of social facts on material facts—that is, facts that are not about human individuals. In this article, I discuss Brian Epstein’s “materialism” in The Ant Trap: granting Epstein’s strict definition of individualism, I show that his arguments depend crucially on a generous conception of social properties and social facts. Individualists, however, are only committed to the claim that projectible properties are individualistically realized, and materialists have not undermined this claim.

Adaptationism is often taken to be the thesis that most traits are adaptations. To assess this thesis, it seems we must be able to establish either an exhaustive set of all traits or a representative sample of this set. Either task requires a more systematic and principled way of individuating traits than is currently available. Moreover, different trait individuation criteria can make adaptationism turn out true or false. For instance, individuation based on natural selection may render adaptationism true, but may do so by presupposing adaptationism. In this article, we show how adaptationism depends on trait individuation and that the latter is an open and unsolved problem.

Simple random-sampling resolutions of the raven paradox relevantly diverge from scientific practice. We develop a stratified random-sampling model, yielding a better fit and apparently rehabilitating simple random sampling as a legitimate idealization. However, neither accommodates a second concern, the objection from potential bias. We develop a third model that crucially invokes causal considerations, yielding a novel resolution that handles both concerns. This approach resembles Inference to the Best Explanation (IBE) and relates the generalization’s confirmation to confirmation of an associated law. We give it an objective Bayesian formalization and discuss the compatibility of Bayesianism and IBE.

Experimental archaeology is often understood both as testing hypotheses about processes shaping the archaeological record and as generating tacit knowledge. Considering lithic technologies, I examine the relationship between these conceptions. Experimental archaeology is usefully understood via “maker’s knowledge”: archaeological experiments generate embodied know-how enabling archaeological hypotheses to be grasped and challenged, and further, well-positioning archaeologists to generate integrated interpretations. Finally, experimental archaeology involves “material speculation”: the constraints and affordances of archaeologists and their materials shape productive exploration of the capacities of objects and human skill in ways relevant to archaeological questions.

This paper concerns the recent revival of entity realism. Having been started with the work of Ian Hacking, Nancy Cartwright, and Ronald Giere, the project of entity realism has recently been developed by Matthias Egg, Markus Eronen, and Bence Nanay. The paper opens a dialogue among these recent views on entity realism and integrates them into a more advanced view. The result is an epistemological criterion for reality: the property-tokens of a certain type may be taken as real insofar as only they can be materially inferred from the evidence obtained in a variety of independent ways of detection.

There is a sense in which a philosophic theory can be confirmed. We may ask what its effects were on the development of scientific theory,—did it clarify ideas and help open up new areas of research, or did it constrain the work of science? In this essay, we shall try to judge the significance of dialectical materialism from this standpoint. We shall be concerned with the bearing of this philosophy on scientific work, especially in the Soviet Union.

Now dialectical materialism is not a “philosophy” in the same sense which the word has when applied to, let us say, logical empiricism. The difference is evident when a writer like Haldane asks, for instance, how far scientific discoveries have verified the principles of dialectical materialism.' We could not ask in a similar way whether scientific discoveries have confirmed the principles of logical empiricism. For the latter affirms no factual propositions concerning the world; it enunciates solely the principle of verifiability, and there is clearly no scientific discovery which could possibly refute the requirement of verification. If it makes sense to ask how far scientific discoveries verify dialectical materialism, then the latter must obviously contain factual propositions concerning nature which should be stated in a way to permit of confirmation of rejection.

The concept of simultaneity, and the associated problems of synchronization of moving clocks and establishment of a universal time scale, were given little or no attention prior to the twentieth century. In 1905, however, Einstein analyzed the concept of simultaneity on the basis of two principal postulates:

1. (1) Absolute velocity is meaningless (relativity postulate),

2. (2) The velocity of light in a vacuum is the same for all unaccelerated observers.

1. Introduction. Professor Nagel's account of the “cognitive status” of scientific theories has been attacked by P. K. Feyerabend [5] and M. B. Hesse [8] in terms of his alledgedly misguided distinction between experimental laws and theories. The difficulty lies, these critics agree, in Nagel's attempt to find a stable basis for scientific theories in an observational basis of experimental laws. Both Feyerabend and Hesse note the vacillation in Nagel's account of the stability of the meaning of experimental terms and in his discussion of the status of observational as opposed to theoretical terms. They find Nagel too “positivistic” and see as a first step toward a more adequate account of scientific theories the abandonment of the theoretical-observational dichotomy as having more than a pragmatic significance. Nagel's discussion of the theoretical-observational dichotomy is, I agree, inadequate in certain respects. I shall, however, suggest a quite different remedy from those of Feyerabend and Hesse, one that depends neither on a phenomenalistic reduction of theoretical entities nor on a blurring of the theoretical-observational dichotomy.

Prior to the advent of evolutionary theory the Natural System was generally conceived as based on “distinctions of kind, not consisting in a given number of definite properties” (J.S. Mill). It was considered final and unique, to be arrived at by more than one approach. Evolutionary theory has shifted emphasis to different characters, yet explicitly or implicitly the belief in a final natural system in biology persists in many textbooks and taints research. Allegedly natural systems are shown to be fundamentally arbitrary and artificial, dependent on numerous value judgments and intrinsically conflicting to varying degrees. Because of this and because it has turned into a bar to clear thinking, the adjective “natural” should be abolished.

Since the collapse of the ‘received view’ consensus in the late 1960s, the question of scientific realism has been a major preoccupation of philosophers of science. This paper sketches the history of this debate, which grew from developments in the philosophy of language, but eventually took on an autonomous existence. More recently, the debate has tended towards more ‘local’ considerations of particular scientific episodes as a way of getting purchase on the issues. The paper reviews two such approaches, Fine's and Hacking's, describing their positions, their prospects, and how they are related. Finally, the paper suggests that local philosophies of science offer a way for our discipline to engage more fruitfully with the public and the scientific community.

When we consider closely any highly integrated vital process, like embryonic development, or animal behavior of the end-subserving or purposive type, we are inevitably impressed with the importance of those special controlling factors, collectively termed “regulative,” which appear chiefly responsible for the unified and finalistic character of the whole sequence of events. These factors are persistent in their influence although they may act intermittently. Without their presence the sequence would soon lose coördination and “run wild,” just as an automobile runs off the road unless occasional compensating touches are given to the steering wheel. They are the factors which give unity and direction to the total process. Generalizing, we may say that in any complex unified process, especially a synthetic one—where the progress is from less to greater complexity—integration seems always to imply or presuppose the operation of regulative factors having the character which we call directive. These keep the sequence of events to a definite course which in the living organism usually terminates in some outcome having special biological significance, or survival value.

Physical theories continue to be interpreted in terms of particles. The idea of a particle has required modification for successive theories but remains central to scientific explanation. Particle ontologies also have the virtue of explaining basic epistemic features of the world and so remain appealing for the scientific realist. However, particle ontologies are untenable when coupled with the empirically necessary postulate of permutation invariance—the claim that permuting the roles of particles in a representation of a physical state results in a representation of the same state. I demonstrate that any permutation invariant theory is incompatible with a particle ontology.

An intuitive idea concerning degrees of precision is widely accepted, and it is that we increase precision of theories by paying attention to ever decreasing orders of magnitude of measurements which we incorporate in these theories. We increase precision of measuring or of predicting measurement of length, for instance, if we pay attention not only to centimeters but also to millimeters, microns, angstroms, and so on. And our theories are precise to centimeters, then to millimeters, and so on respectively. The idea is that increased precision is the process of capturing a point within nested intervals, and that this is reflected both in experimental and in theoretical progress. An intuitive analogy may be drawn with series of photos made by a camera which approaches the moon's surface. A corollary from this intuitive idea which has been stated by a number of writers is that observation reports and theories are not overthrown even when superseded by more accurate observation because within the limits of their own precision-range they are still valid. When a law in physics is stated, it is stated usually without such qualifications; but this is a mere matter of convenience, we are told. The idea is that a tacit proviso is understood and the law should be understood to be not the statement “such and such is the case” but the statement “within this and that limit of accuracy such and such is the case”; in such a formulation, the law, once verified, remains unshaken regardless of further progress in the field.

Jerry Fodor has recently proposed a new entry into the list of information based approaches to semantic content aimed at explicating the general notion of representation for both mental states and linguistic tokens. The basic idea is that a token means what causes its production. The burden of the theory is to select the proper cause from the sea of causal influences which aid in generating any token while at the same time avoiding the absurdity of everything's being literally meaningful (since everything has a cause). I argue that a detailed examination of the theory reveals that neither burden can be successfully shouldered.

Sexes are normally taken to be fundamental categories in biology—many sexually reproducing organisms fall under the categories of female/male. Much research aims at explaining differences between sexes. Sexual selection forms a central framework for explaining “typical” distributions of traits among sexes and explicating circumstances leading to “reversal.” I claim that sexual selection models need not make use of sexes and that sexes lack explanatory significance in such models. I offer a framework of reproductive dimorphism and argue that it is better than that of sexes because it (1) is more compatible with explanations of sexual selection and (2) allows for their greater applicability.

The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable approximations to Solomonoff prediction do not always converge.

Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have advanced a possibilist interpretation: climate models stand in for possible scenarios that could occur but do not provide information about how probable those scenarios are. This article argues that possibilism is (1) undermotivated, (2) incompatible with successful practices in the science, and (3) unable to correct for known biases. The upshot is that the models should be interpreted probabilistically in at least some cases.