In this paper we examine the pattern of conceptual change during scientific revolutions by using methods from cognitive psychology. We show that the changes characteristic of scientific revolutions, especially taxonomic changes, can occur in a continuous manner. Using the frame model of concept representation to capture structural relations within concepts and the direct links between concept and taxonomy, we develop an account of conceptual change in science that more adequately reflects the current understanding that episodes like the Copernican revolution are not always abrupt. When concepts are represented by frames, the transformation from one taxonomy to another can be achieved in a piecemeal fashion not preconditioned by a crisis stage, and a new taxonomy can arise naturally out of the old frame instead of emerging separately from the existing conceptual system. This cognitive mechanism of continuous change demonstrates the constructive roles of anomaly and incommensurability in promoting the progress of science.

I consider the problem of extending Reichenbach's principle of the common cause to more than two events, vis-à-vis an example posed by Bernstein. It is argued that the only reasonable extension of Reichenbach's principle stands in conflict with a recent proposal due to Horwich. I also discuss prospects of the principle of the common cause in the light of these and other difficulties known in the literature and argue that a more viable version of the principle is the one provided by Penrose and Percival (1962).

Callender and Cohen argue that there is no need for a special account of the constitution of scientific representation. I argue that scientific representation is communal and therefore deeply tied to the practice in which it is embedded. The communal nature is accounted for by licensing, the activities of scientific practice by which scientists establish a representation. A case study of the Lotka-Volterra model reveals how licensure is a constitutive element of the representational relationship. Thus, any account of the constitution of scientific representation must account for licensing, meaning that there is a special problem of scientific representation.

The historical origin and the experimental basis of the concept of physical determinism indicate that this basis was removed with the acceptance of the kinetic theory of matter, while its difficulties are increased by the admission that human nature, in its entirety, is a product of natural causation. An indeterministic view of causation has the advantages (a) of unifying the concept of natural law in different spheres of human experience and (b) of a greater generality, which precludes the acceptance of the special case of completely deterministic causation, so long as this is an unproved assumption. It is not inconsistent with the orderliness of the world, or with the fruitful pursuit of natural knowledge. It enriches rather than weakens the concept of of causation. It possesses definite advantages with respect to the one-sidedness of human memory, and to the phenomena of aiming and striving observable in man and other animals. Among biological theories it appears to be most completely in harmony with the theory of natural selection, which in its statistical nature resembles the second law of thermo-dynamics.

In an indeterministic world natural causation has a creative element, and science is interested in locating the original causes of effects of special interest, and not merely in pushing a chain of causation backwards ad infinitum. These contrasting tendencies are illustrated by a critique of the mutation theory, and by an attempt more closely to define the sense in which indeterministic causation should be thought of as creative.

We argue that ‘locality’, perhaps the most mundane term in ecology, holds a basic ambiguity: two concepts of space—nomothetic and idiographic—which are both necessary for a rigorous resurvey to “the same” locality in the field, are committed to different practices with no common measurement. A case study unfolds the failure of the standard assumption that an exogenous grid of longitude and latitude, as fine-grained as one wishes, suffices for revisiting a species locality. We briefly suggest a scale-dependent “resolution” for this replication problem, since it has no general, rational solution.

Various formulations of the principle of simplicity in science are examined and rejected in favor of Goodman's proposal, the essence of which is to concentrate attention upon the predicates that form the extralogical basis of any given theory and to provide measures for comparing the relative structural simplicity of different sets of such predicates. The postulational basis of Goodman's method is set out and explained, together with some important amendments and additions, and a number of theorems are proved, with whose aid the simplest theory to account for a certain corpus of scientific phenomena is readily determinable.

Peter Achinstein gives in his papers [1] and [2] interesting analyses of some problems of inductive logic and of some approaches I have proposed. I shall discuss here some of these problems in order to clarify my present position. My comments will mainly concern the variety of instances, and only briefly the analogy influence, and the inductive methods for a coordinate language.

The discovery that some B vitamins are constituents of respiratory coenzymes led to the development of an interfield theory of the kind discussed by Darden and Maull (1977). In this paper it is shown that the development of a useful interfield connection was made possible by two reconceptualizations: (1) a re-conceptualization that united two then-distinct fields giving rise to the concept of vitamins as dietary substances; and (2) another reconceptualization that united two approaches to respiratory metabolism producing the idea that coenzymes are transport vehicles.

The question, what a given statement is “about,” often occurs in philosophic discussion. I shall use this question in the hope of illustrating how a relatively simple application of symbolic logic can clarify a problem which might otherwise turn into a maze of complications.

Model simplicity in curve fitting is the fewness of parameters estimated. I use a vector model of least squares estimation to show that degrees of freedom, the difference between the number of observed parameters fit by the model and the number of explanatory parameters estimated, are the number of potential dimensions in which data are free to differ from a model and indicate the disconfirmability of the model. Though often thought to control for parameter estimation, the AIC and similar indices do not do so for all model applications, while goodness of fit indices like chi-square, which explicitly take into account degrees of freedom, do. Hypothesis testing with prespecified values for parameters is based on a metaphoric regulative subject/object schema taken from object perception and has as its goal the accumulation of objective knowledge.

Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence (OI)—when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a sufficient independence condition for warranting robustness arguments. We show that OI evidence can collectively confirm a hypothesis to a lower degree than individual lines of evidence, contrary to the standard assumption undergirding usual robustness arguments. We employ Bayesian networks to represent the ideal empirical scenario for a robustness argument and a variety of ways in which empirical scenarios can fall short of this ideal.

This essay explores the connection between representation and explanation in the sciences. I suggest that scientific representation schemes be viewed as pragmatic tools for acquiring the sort of articulated awareness that is the hallmark of nontrivial knowledge. Crystal field theory in chemistry illustrates this perspective. Certain representations achieve the status of being paradigmatically explanatory, thereby shaping models of intelligibility. In turn, these explanatory preferences serve largely to define and differentiate disciplinary communities by implicitly endorsing particular epistemic aims and values. In this way, the pragmatic nature of explanatory discourse effectively grants its intellectual utility.

Biological reproduction is a material process of intertwined, recursive propagule generation and development, assuming that development produces simple life cycles. Most organisms, however, have more or less complex life cycles. Here, I attempt to reconcile recent articulations of a reproducer account with traditional approaches to complex life cycles by generalizing genetic demarcation criteria for life cycle generations in terms of the “scaffolded” development of hybrid reproducers. I argue that scaffolding provides a general method for identifying developmental bottlenecks and suggests in turn a new way of understanding developmental reaction norms.

P. Kyle Stanford defends the problem of unconceived alternatives, which maintains that scientists are unlikely to conceive of all the scientifically plausible alternatives to the theories they accept. Stanford's argument has been criticized on the grounds that the failure of individual scientists to conceive of relevant alternatives does not entail the failure of science as a corporate body to do so. I consider two replies to this criticism and find both lacking. In the process, I argue that Stanford does not provide evidence that there are likely scientifically plausible unconceived alternatives to scientific theories accepted now and in the future.

While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under which (approximately) Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics.

Imagination is important for many things in science: solving problems, interpreting data, designing studies, and much else. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, for example, by self-imposed rules to infer logically or model events accurately. But the constraints offered by these philosophers constrain either too much or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy.

Confirmation theorists seek to define a function that will take into account the various factors relevant in determining the degree to which an hypothesis is confirmed by its evidence. Among confirmation theorists, only Rudolf Carnap has constructed a system which purports to consider factors in addition to the number of instances, viz. the variety manifested by the instances and the amount of analogy between the instances. It is the purpose of this paper to examine the problem which these additional factors raise for confirmation theory, and to prove that, despite Carnap's claim, no confirmation function satisfying the requirements he has specified can take account of variety and analogy. This result is first proved for a special case, and then, in a subsequent section, is generalized through the introduction of a theorem (the proof of which is given in Appendix I). In the final section of the paper it is shown that, contrary to a claim which Carnap has made, not even the concept of the “logical width” of a predicate will enable confirmation functions satisfying his requirements to take adequate account of analogies between instances.

A gas prepared in a nonequilibrium state will approach equilibrium and stay there. An influential contemporary approach to statistical mechanics explains this behavior in terms of typicality. However, this explanation has been criticized as mysterious as long as no connection with the dynamics of the system is established. We take this criticism as our point of departure. Our central claim is that Hamiltonians of gases that are epsilon-ergodic are typical with respect to the Whitney topology. Because equilibrium states are typical, it follows that typical initial conditions approach equilibrium and stay there.

Biology lacks a central organism concept that unambiguously marks the distinction between organism and non-organism because the most important questions about organisms do not depend on this concept. I argue that the two main ways to discover useful biological generalizations about multicellular organization—the study of homology within multicellular lineages and of convergent evolution across lineages in which multicellularity has been independently established—do not require what would have to be a stipulative sharpening of an organism concept.