The thesis of this paper is that in dealing with problems of "mind," the philosopher of mind needs to be as well grounded in his relevant sciences (e.g. psychology, anthropology) as the philosopher of the physical sciences needs to be grounded in his relevant sciences (e.g. physics). The thesis of this paper is also that the psychological analysis of solipsism and the philosophical analysis are not independent (or at least not independent in all of their aspects), and that therefore the (...) psychological analysis sheds light on the philosophical, and vice versa. It is argued that solipsism is untenable on at least two grounds: because (1) there are no such physical phenomena as acts of "immediate perception," and because (2), that there can be no such thing as an "individual mind" without some form of a "group mind.". (shrink)

In moments of daring, some physical scientists consider problems of social inquiry, hoping naively that the methods of physical inquiry will provide them with special insight. In my own work on problems of industrial production where I am searching for “practical” means for optimizing production in some socially satisfactory sense, I find that the physical scientist cannot escape the responsibility for social inquiry. So far as I can understand the nature of this work, it requires for its fruitful pursuit a (...) methodology which leans heavily on the concepts of statistical control of Shewhart, of cybernetics of Wiener and of experimentalism of Singer, Churchman and Ackoff. (shrink)

1. Deductive and Inductive Inference. Within the traditional treatments of scientific method, e.g., in and, it was customary to divide scientific inference into two parts: deductive and inductive. Deductive inference was taken to mean the activity of deducing theorems from postulates and definitions, whereas inductive inference represented the activity of constructing a general statement from a set of particular “facts.” Deductive inference was relegated to the mathematical sciences, and inductive inference to the empirical sciences. As a consequence, the whole of (...) science was split into two quite distinct parts: deductive science was conceived to start with precise axioms, postulates, and definitions, and its method consisted in drawing inferences from these “givens” in such a way that if the original assumptions are taken as true, then the theorems must be taken as true also. The obligation behind this “must” of the mathematical sciences was an obligation based on strict rules of deductive inference; in the earlier analyses, it was supposed that these rules were all aspects of the general theory of the syllogism, as it was described in an almost complete form in but in later work the rules have been formalized in more general terms. Inductive inference, on the other hand, was supposed to start with observed facts; these facts, or “data,” were presumably given by the senses, and described particular aspects of the external world. If the facts were given in a certain way, then the empirical scientist could “infer” a generalized description; this generalization had the characteristic that if it were granted as true, then all the facts could be deduced as consequences. The inductive process admittedly does not lead to unique generalizations, and the philosopher of science searched for other defining characteristics of good inference, such as “simplicity” and “convenience.” These empirical generalizations were taken to be “descriptions of the phenomenal world of the scientist”; a further inductive step might be taken by constructing a set of very general principles out of the more specialized generalizations within specific research problems. These “higher” inductive inferences were regarded as “theories,” which could be studied by themselves within the method of deductive inference. The scientist was then described as “checking” theory by determining whether or not the predicted consequences deduced from theory actually hold in the phenomenal world. (shrink)

This article argues that the controversy over genetically modified crops is best understood not in terms of the supposed bias, dishonesty, irrationality, or ignorance on the part of proponents or critics, but rather in terms of differences in values. To do this, the article draws on and extends recent work of the role of values and interests in science, focusing particularly on inductive risk and epistemic risk, and it shows how the GMO debate can help to further our understanding of (...) the various epistemic risks that are present in science and how these risks might be managed. (shrink)

The purpose of this paper is to show that there are as many formulations of the process of falsification as there are archetypal, philosophical systems of inquiry. This paper explores several systems of inquiry which are based on Churchman's reading of the history of Western epistemology. It is argued that (1) the falsification of scientific theories can never be a purely formal process although it is perpetually open to formal exploration; (2) that contrary to current belief, falsification can never be (...) more certain than confirmation because falsification involves judgments which are no more certain than those involved in confirmation. The supposed asymmetry between confirmation and falsification is severely challenged. Finally, a Feyerabendian and a Hegelian notion of falsification are explicitly developed and contrasted. (shrink)

The intention of the present essay is to urge a reconsideration of the Realism-Phenomenalism-Issue, mainly and primarily in regard to the interpretation of scientific hypotheses; secondarily also relating to the basic problems of epistemology.

Kevin Elliott and others separate two common arguments for the legitimacy of societal values in scientific reasoning as the gap and the error arguments. This article poses two questions: How are these two arguments related, and what can we learn from their interrelation? I contend that we can better understand the error argument as nested within the gap because the error is a limited case of the gap with narrower features. Furthermore, this nestedness provides philosophers with conceptual tools for analyzing (...) more robustly how values pervade science. (shrink)

A common complaint against the increasing privatization of research is that research that is conducted with the immediate purpose of producing applicable knowledge will not yield knowledge as valuable as that generated in more curiosity‐driven, academic settings. In this paper, I make this concern precise and reconstruct the rationale behind it. Subsequently, I examine the case of industry research on the giant magnetoresistance effect in the 1990s as a characteristic example of research undertaken under considerable pressure to produce applicable results. (...) The example permits one to arrive at a more optimistic assessment of the epistemic merits of private, application‐driven research. I attempt to specify the conditions that, in this case, advanced the production of interesting and reliable knowledge. (shrink)

Several authors have recently contended that modern statistical theory provides a powerful argument in favor of the view that if scientists accept or reject hypotheses at all they do so only in a behavioral sense--i.e., in a sense which reduces "accepting P" to "acting on the basis of P relative to an objective O". In this paper, the argument from statistics in favor of a behavioral view is outlined; an interpretation of two statistical procedures (Bayes method and signifigance testing) is (...) offered which does not entail a behavioral analysis of "accepting a hypothesis"; and the conclusion that non-behavioral analyses of belief are compatible with the application of current statistical theory in the sciences is tentatively advanced. (shrink)

Using pure statistical evidence about a group to judge a particular member of that group is often found objectionable. One natural explanation of why this is objectionable appeals to the moral notion of respecting individuality: to properly respect individuality, we need individualized evidence, not pure statistical evidence. However, this explanation has been criticized on the ground that there is no fundamental difference between the so-called “individualized evidence” and “pure statistical evidence”. This paper defends the respecting-individuality explanation by developing an account (...) of what it means to respect individuality. It combines an idealistic account of respecting individuality and a prioritization account of respecting individuality, and offers a principled way to distinguish individualized evidence from non-individualized evidence. (shrink)

The science of the 19th and early 20th century permitted the view that all human experience is subject to the deterministic laws of physics. Reality was conformable with these laws, and the laws could be used to designate what is real.

1. Objective of the Paper. This is an exercise in formalism; an attempt to see what a certain hypothesis would look like if it were spelled out in more detail than it has so far received. The object is to frame a self-consistent hypothesis that includes certain contributions of both optimism and pessimism. We would like to save the moral advantages of each position; at first glance they seem logically exclusive.