One component of a viable account of scientific inquiry is a defensible conception of scientific problems, i.e., a conception which meets logical demands and which also fits or explains basic “data” arising from the history of that inquiry, including an account of how problems arise. In this paper I shall argue that three standard empiricist models of problems—essentially the logical positivist and Popperian views—satisfy neither the historical requirements nor even the logical conditions (except, weakly, in the case of Popper). These failures are instructive, however. They represent steps toward the solution of the “problem” problem—the problem of developing a model of problems rich enough to account for the data. In the weakest sense (which is all I need), ‘accounting for’ a datum means explaining how that aspect of scientific inquiry is possible. I shall not have space here to consider promising recent work on problems by Laudan (1977) and others.

Kuhn (1962), Lakatos (1978) and Laudan (1977) all subscribe to a view of science which admits the existence of large scale entities differing from theories. Kuhn called these entities ‘paradigms’, Lakatos called them ‘research programs’ and Laudan calls them ‘research traditions’. These entities are distinguished from theories by their historical durability and the unique manner in which they succeed one another. The history of science may be described as a succession of eras during each of which one (or more) of these entities was dominant. During its era of dominance one of these entities may support several incompatible theories which replace one another successively but share certain common features. These features may be (part of) a common ontology, a common set of epistemological standards employed in gathering observational evidence, or common methodological or conceptual directives employed in solving new scientific problems. Although theories may change, these features (or some of these features) do not, instead they are the province of the large scale entity.

If science is essentially a problem-solving activity, it stands to reason that a good part of the rationale behind the development and growth of new scientific fields (or subfields) is the generation of problem-solutions. I should like to argue that the origin and, especially, the development of new scientific fields is primarily a research procedure for solving existing unsolved problems and generating and solving new unsolved problems. By a scientific field I have in mind the following:

In the present work, I discuss the interpretation of quantum mechanics (QM) from the viewpoint of quantum logic (QL). I regard the objects of QL to be the possible (accidental) properties that can be ascribed to a quantum system SYS. The basic idea is that, at any given moment t, SYS actualizes some properties, but not others. The micro-state of SYS at time t is identified with the set of all properties that SYS actualizes at time t.

One thing an interpretation of QM is supposed to do, I believe, is delineate the admissible quantum micro-states. Since the characterization of quantum micro-states is intimately related to the characterization of quantum logical consistency, the interpretation of QM is intimately tied to the interpretation of QL.

Two kinds of interpretations are discussed. Strict interpretations are based on the assumption that the properties of a system are individuated by the projection operators on the associated Hilbert space.

There is no such thing as “The Quantum Logical Interpretation of Quantum Mechanics”. Rather, there is a cluster of interpretations, all of which can be described as “quantum logical”. Here I provide a general framework for discussing interpretations of this kind, and then locate various suggestions within it. The presentation owes much to van Fraassen (see, in particular, van Fraassen 1974 ); his “modal interpretation” is one of those I discuss, along with those of Jauch, Putnam and Kochen. I begin by rehearsing some orthodox quantum theory.

Within quantum mechanics we deal with a set 0 of measurable quantities, or observables (position, momentum, components of spin and so on). Experiment can determine the value of an observable for a given system: the values so determined will be real numbers. A maximal amount of information about what the result would be for a given system, whatever experiment we chose to perform on it, is available once we know the state of the system.

There is no more popular pastime in the literature of the philosophy of biology than analyzing the concept of species. This is partly due to the fact that the concept is such a prominent one in presentations of evolutionary theory. It is also a result of the fact that philosophers and biologists have struggled without a great deal of success to formulate a definition of species that would be acceptable for all the diverse purposes of the biological sciences.

For some time, philosophers of biology assumed that, whatever problems of definition and explication exist regarding the concept of a species, the ontological status of the concept was certain. Species have long been viewed as classes. Indeed, they have been viewed as paradigmatic examples of classes of a special variety. Since the traits of organisms vary from creature to creature as well as from generation to generation, a special set of properties must be used to group or aggregate organisms into species.

The Darwinian theory of evolution through natural selection is beyond a doubt an extremely well established theoretical edifice that satisfies any reasonable conceptual and empirical criterion of scientific respectability. It is a body of well confirmed nomological generalizations with great explanatory and predictive power. And yet the most accessible account of the relation between this theory, its competitors and the empirical evidence seems seriously defective in its account of these relations. Indeed, it may seem so defective as to leave the question open, not whether the theory of natural selection is well confirmed (this cannot be doubted), but exactly what sort of evidence does confirm it and via what bridge principles. The account of the matter which I have described as most accessible (in the philosophy of science at any rate), and yet seriously bedeviled is to be found in Michael Ruse's otherwise excellent introduction to the Philosophy of Biology (Ruse 1973 ).

The foundations of a number of scientific theories are more or less relevant to philosophy. The better a theory is at elucidating the structure of science and scientific method the more a study of its foundations is relevant for philosophers, particularly philosophers of science. But while philosophers have studied probability and induction, statistics has not received the kind of philosophical attention mathematics and physics have. Although the terms “philosophy of induction” and “confirmation theory” are common, the term “philosophy of statistics” is rarely used; and despite the fact that modern statistical methods have been used increasingly in a number of sciences, specific developments of statistics have been little noted in the philosophy of science literature.

Statistics has been fundamental for determining such things as whether a substance causes cancer, which method of psychotherapy gives the most recoveries, whether censorship causes the instability of nations, whether a fossil belongs to a man or a chimpanzee, whether there is regularity in the oscillations of the velocity of gas in the sun's atmosphere, whether an individual authored a piece of writing, whether the economy will improve, and numerous other issues involving uncertainties.

What is at issue between the propensity and the long run frequency schools of thought about objective probability? Recent debate, although vigorous, has contributed little to our understanding of natural law or statistical inference. Yet there is at least one real question, none other than the much maligned topic of emergentism. Although this invokes a number of metaphysical views, such as the unity of science, emergentism primarily poses a question of matter of fact. Is it the case that every stable frequency, correctly represented by a mathematical probability, is ‘grounded from below’ by probabilities that apply to individuals? That is, does the frequency distribution in the population derive from probabalistic facts about the individuals that compose it? Or are there some stable frequencies that pertain to populations, but do not derive from probabalistic facts about members of the population?

At least two approaches to these questions have been developed.

Much work in confirmation theory is directed towards finding or interpreting a function, c, taking on hypotheses and evidence as its arguments and returning a value by which the degree of support of the evidence for the hypothesis can be assessed. Confirmation functions are generally thought of as probability functions. That is, c(H,E) is thought to obey the axioms of probability theory, where H is an hypothesis and E the evidence being considered. A difficulty with this approach is that the various problems of induction, including Hume's and Goodman's, militate against construing any confirmation function as a probability function. To date, no satisfactory probability function has been found which addresses the general problem of ampliative inference and which is immune to the standard objections of the Humean or Goodmanian type.

These sorts of considerations suggest it would be promising to examine, as candidates for an acceptable confirmation function, functions which are not probability functions.

Almost since the theories of Einstein and the quantum physicists came into being, a small but significant number of novelists, poets, and playwrights have turned to them for everything from casual metaphors to justification for the philosophies underlying their works. Until fairly recently, however, literary critics have tended to avoid the new physics, finding it uncongenial if not irrelevant. But over the last twenty-five years an increasing number of them, especially critical theorists, have turned to physics and even philosophy of science in the belief that these disciplines offer epistemological and methodological models applicable, to the problems of literary criticism.

The primary reason for this increased interest in philosophy of science is the rise of critical formalisms, particularly structuralism and its variants. Structuralism usually regards Russian formalism as its most significant precursor, but Northrop Frye's Anatomy of Criticism (1957) must also be seen as an important forerunner, since it provided formal criticism with a rationale.

Literary study, along with other social sciences, has been thought by many to be incapable of progress because it, like the other social sciences, is culturally defined. The aims and standards of literary study always depend on the value assumptions and preconceptions of the culture which fosters literary study—for literary study is a social institution. Because literary study and other social sciences are social institutions, obvious difficulties arise with transplanting the aims and standards of social science in one society into another society. The idea of progress, however, appears to demand that we have aims and standards which apply independently of particular social contexts, and independently of the boundaries of a culture or an age. Thus the cultural definition of literary study has sometimes been thought to prevent progress in this field.

Max Weber proposed a strategy for working toward objective knowledge and progress in the social sciences generally, which can be applied to literary study.

The problem of the reduction of biology to physical chemistry has raised numerous controversies for several years. The reader is referred to Ayala & Dobzhansky (1974), Hull (1972, 1973, 1974, 1976), Polanyi (1967, 1968), Roll-Hansen (1969, 1974), Ruse (1971, 1976), and Schaffner (1967, 1969, 1974, 1976). Supporters and opponents of reduction are continually exchanging arguments and it is almost impossible, even for an objective reader, to discern who is correct.

The partisans of reduction insist that physical chemistry, contributes a very useful explanatory schema for the understanding of a certain number of biological processes. For instance, in genetics, great progress has been realized because of the contribution made by chemistry in the determination of the genetic code and in the understanding of the molecular mechanisms governing the laws of heredity.

An often heard remark is that “discovery of the molecular basis of heredity means that all life processes are now or will shortly be explainable on a molecular basis.” This extreme view is defended with surprising vehemence by one faction of biologists. The opposing view, just as extremely expressed is that “no interesting biological phenomena have yet been explained by molecular mechanisms, not even genetic phenomena.” These two positions have been called the “reductionist” and “antireductionist” points of view. Since “reductionism” is given in the philosophy of science many different meanings, we choose the one which in our opinion could shed some light on the problems underlying this controversy. In our view all the emotion-laden epithets aside, “reductionism” has still primarily to do with “theory reduction” in the logical empiricist (or positivist) sense. Clearly this concept is inextricably tied up with that of “explanation”, and fundamentally it is explanations that this controversy is about.

Contemporary psychology has been dominated by two distinct paradigms, each of which have given rise to comprehensive and fruitful research programmes. The functionalist programme purports to explain our cognitive capacities — what Noam Chomsky (1965, pp. 3 ff.) dubs our “competence” — in terms of the operations and transformations effected on the available “information”. Explaining, e.g., an ability such as color perception means isolating the cues on which we rely in making our judgments as to color, and proceeding to explain how, on the basis of information available from such cues, we could come to reach our actual judgments. This will involve explaining, for example, how it is that our perceptions of color are constant and reliable despite substantial variation in the intensity of light impinging on the retina — particularly since the intensity of such light seems to be the only relevant parameter which could guide our judgments.

By “evolutionary epistemology” I mean Darwinian models of the growth of scientific knowledge. Such models rely on analogies between the development of biological species and the development of scientific theories. Recent proponents of evolutionary epistemology include the psychologist Donald Campbell (1974a), the sociobiologist Richard Dawkins (1976), and philosophers of science Karl Popper (1972), Stephen Toulmin (1972), and Robert Ackerman (1970). I shall argue that the similarities between biological and scientific development are superficial, and that clear examination of the history of science shows the need for a non-Darwinian approach to historical epistemology.

The neo-Darwinian model of species evolution consists of Darwin's theory of natural selection synthesized with twentieth century genetic theory. The central ingredients of the neo-Darwinian model are variation, selection and transmission. Genetic variations occur within a population as the result of mutations and mixed combinations of genetic material.

Although Barry Barnes (1974, 1977) and David Bloor (1976, 1978, 1981) are co-workers in the Science Studies Unit at the University of Edinburgh, there are hitherto unnoted but fundamental differences in their programs in the sociology of science.

Bloor defines his “strong programme” in the sociology of science by three basic tenets (“causality,” “symmetry,” and “reflexivity”) and also claims to establish laws and to test a general theory of the causal links connecting cognitive and social factors in the history of science. (Bloor 1976, pp. 4-5). In other words, the “strong programme” aims to be: (1) Causal, i.e., concerned with the conditions which bring about beliefs or states of knowledge. (2) Symmetrical, i.e., appealing to the same sorts of causes and to the same patterns of causal explanation for all beliefs and cognitive claims, whether regarded as true or false, rational or irrational, successful or unsuccessful. (3) Reflexive, i.e., using the explanatory resources of the sociology of science in the critical evaluation and explanation of the sociology of science itself.