The doctrine that the character of our perceptual knowledge is plastic, and can vary substantially with the theories embraced by the perceiver, has been criticized in a recent paper by Fodor. His arguments are based on certain experimental facts and theoretical approaches in cognitive psychology. My aim in this paper is threefold: (1) to show that Fodor's views on the impenetrability of perceptual processing do not secure a theory-neutral foundation for knowledge; (2) to show that his views on impenetrability are almost certainly false; and (3) to provide some additional arguments for, and illustrations of, the theoretical character of all observation judgments.

Churchland's paper “Perceptual Plasticity and Theoretical Neutrality“ offers empirical, semantical and epistemological arguments intended to show that the cognitive impenetrability of perception “does not establish a theory-neutral foundation for knowledge” and that the psychological account of perceptual encapsulation that I set forth in The Modularity of Mind “[is] almost certainly false“. The present paper considers these arguments in detail and dismisses them.

This paper challenges some leading views about the conditions under which the ascription of beliefs and desires can make sense of, or provide reasons for, a creature's behavior. I argue that it is unnecessary for behavior to proceed from beliefs and desires according to the principles of logic and decision theory, or even from principles that generally get things right. I also deny that it is necessary for behavior to proceed from principles that, though perhaps subrational, are similar to those that we ourselves use. I then propose some conditions that are considerably weaker, and argue that they fulfill the descriptive and explanatory requirements of intentional ascription.

A tempting argument for human rationality goes like this: it is more conducive to survival to have true beliefs than false beliefs, so it is more conducive to survival to use reliable belief-forming strategies than unreliable ones. But reliable strategies are rational strategies, so there is a selective advantage to using rational strategies. Since we have evolved, we must use rational strategies. In this paper I argue that some criticisms of this argument offered by Stephen Stich fail because they rely on unsubstantiated interpretations of some results from experimental psychology. I raise two objections to the argument: (i) even if it is advantageous to use rational strategies, it does not follow that we actually use them; and (ii) natural selection need not favor only or even primarily reliable belief-forming strategies.

A common view among statisticians is that convergence (which statisticians call consistency) is a necessary property of an inference rule or estimator. In this paper, this view is challenged by appeal to an example in which a rule of inference has a likelihood rationale but is not convergent. The example helps clarify the significance of the likelihood concept in statistical inference.

Taxonomies of living things and the methods used to produce them changed little with the institutionalization of evolutionary thinking in biology. Instead, the relationships expressed in existing taxonomies were merely reinterpreted as the result of evolution, and evolutionary concepts were developed to justify existing methods. I argue that the delay of the Darwinian Revolution in biological taxonomy has resulted partly from a failure to distinguish between two fundamentally different ways of ordering identified by Griffiths (1974): classification and systematization. Classification consists of ordering entities into classes, groups defined by the attributes of their members; in contrast, systematization consists of ordering entities into systems, more inclusive entities whose existence depends on some natural process through which their parts are related. Evolutionary, or phylogenetic, systematics takes evolutionary descent to be the natural process of interest in biological taxonomy. I outline a general framework for a truly phylogenetic systematics and examine some of its consequences.

The contributions to Testing Scientific Theories are unified by an interest in responding to criticisms directed by Glymour against existing models of confirmation–-chiefly H-D and Bayesian schemas–-and in assessing and correcting the “bootstrap“ model of confirmation that he proposed as an alternative in Theory and Evidence (1980). As such, they provide a representative sample of objections to Glymour's model and of the wide range of new initiatives in thinking about scientific confirmation that it has influenced. The effect is a sense of engagement and focus, and of significant advance at least in articulation of the problems that require solution; as Earman observes, “it is … heartening to report that the various opposing camps learned from each other” (p. vi). In what follows I am concerned to assess what has been learned both critically, about Glymour's model, and constructively about the resources of the alternatives he challenges. My thesis is that while the theories emerging in this debate do deal with a wider range of scientific practice than before, their remaining limitations raise important questions about the ambitions and criteria of adequacy that have traditionally governed philosophical inquiry in this area.