According to Marr, a computational-level theory consists of two elements, the what and the why. This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: (a) that the Why element plays an explanatory role in computational-level theories, (b) that its goal is to explain why the computed function (specified by the What element) is appropriate for a given visual task, and (c) that the explanation consists in showing that the functional relations between the representing cells are similar to the “external” mathematical relations between the entities that these cells represent.

Bayesian probabilistic explication of inductive inference conflates neutrality of supporting evidence for some hypothesis H (“not supporting H”) with disfavoring evidence (“supporting not-H”). This expressive inadequacy leads to spurious results that are artifacts of a poor choice of inductive logic. I illustrate how such artifacts have arisen in simple inductive inferences in cosmology. In the inductive disjunctive fallacy, neutral support for many possibilities is spuriously converted into strong support for their disjunction. The Bayesian “doomsday argument” is shown to rely entirely on a similar artifact.

Whether meaning is compositional has been a major issue in linguistics and formal philosophy of language for the last 2 decades. Semantic holism is widely and plausibly considered as an objection to the principle of semantic compositionality therein. It comes as a surprise that the holistic peculiarities of scientific language have been rarely addressed in formal accounts so far, given that semantic holism has its roots in the philosophy of science. For this reason, a model-theoretic approach to semantic holism in the language of science is presented here. This approach preserves compositionality to a large extent.

The causal theory of reference is often taken to provide a solution to the problems, such as incomparability and referential discontinuity, that the meaning-change thesis raised. I show that Kuhn successfully questioned the causal theory and Putnam's idea that reference is determined via the sameness relation of essences that holds between a sample and other members of a kind in all possible worlds. Putnam's single ‘essential’ properties may be necessary but not sufficient to determine membership in a kind category. Kuhn argued that extension is fixed by similarity-dissimilarity relations that are liable to change in taxonomic reorganizations of science.

This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that constitute deductive calculations based on known probabilities among events. As a result, the ampliative dimension of frequentist induction—learning from data about the underlying data-generating mechanism—is missing.

In a recent Philosophy of Science article, Gerhard Schurz proposes meta-inductivistic prediction strategies as a new approach to Hume's problem. This discussion examines the limitations of Schurz's approach. It can be proved that the meta-inductivistic approach does not work anymore if meta-inductivists have to face an infinite number of alternative predictors. With this limitation it remains doubtful whether the meta-inductivist can provide a full solution to the problem of induction.

In their book What Darwin Got Wrong, Jerry Fodor and Massimo Piattelli-Palmarini construct an a priori philosophical argument and an empirical biological argument. The biological argument aims to show that natural selection is much less important in the evolutionary process than many biologists maintain. The a priori argument begins with the claim that there cannot be selection for one but not the other of two traits that are perfectly correlated in a population; it concludes that there cannot be an evolutionary theory of adaptation. This article focuses mainly on the a priori argument.

Some writers have urged that evolutionary theory produces generalizations that hold only ceteris paribus, that is, provided “everything else is equal.” Others have claimed that all laws in the special sciences, or even all laws in science generally, hold only ceteris paribus. However, if we lack a way to determine when everything else really is equal, hedging generalizations with the phrase “ceteris paribus” renders those generalizations vacuous. In what follows, I propose a solution to this problem for the case of causal equations from classical population genetics. My proviso is generated on the basis of a couple of conceptual maneuvers, “tricks,” which should be usable elsewhere too.

While the question of whether selected-effects accounts of function or causal-role accounts of function provide the ‘true’ functional analysis has given way to a general pluralistic consensus, Philip Kitcher has suggested that different functional accounts allow for unification. I argue that Kitcher's attempt to unify the two functional analyses fails because he adopts the environment-centered perspective on selection as a premise. The premise is undermined by the role niche construction is likely to play in the context of evolution. Moreover, I raise the tentative suggestion that niche construction may threaten the applicability, or at least the relevance, of selected-effects ascriptions.